Login| Sign Up| Help| Contact|

Patent Searching and Data


Title:
ASSESSMENT METHOD
Document Type and Number:
WIPO Patent Application WO/2008/113995
Kind Code:
A1
Abstract:
The present invention relates to a method of assessing the developmental potential of an embryo. The method comprises the steps of incubating the embryo in a culture medium comprising a plurality of amino acids and determining a change in concentration of at least one amino acid in the culture medium. At least one quantifiable morphological and/or kinetic marker is also measured and the data is used to obtain an assessment of the developmental potential of an embryo.

Inventors:
BOOTH PAUL (GB)
LEESE HENRY (GB)
Application Number:
PCT/GB2008/000937
Publication Date:
September 25, 2008
Filing Date:
March 18, 2008
Export Citation:
Click for automatic bibliography generation   Help
Assignee:
NOVOCELLUS LTD (GB)
BOOTH PAUL (GB)
LEESE HENRY (GB)
International Classes:
G01N33/50; G01N33/68; G06F19/00
Foreign References:
US20030091977A12003-05-15
Other References:
BRISON D R ET AL: "Identification of viable embryos in IVF by non-invasive measurement of amino acid turnover", HUMAN REPRODUCTION, IRL PRESS, OXFORD, GB, vol. 19, no. 10, 1 October 2004 (2004-10-01), pages 2319 - 2324, XP009081883, ISSN: 0268-1161
SAKKAS DENNY ET AL: "Noninvasive methods to assess embryo quality", CURRENT OPINION IN OBSTETRICS AND GYNECOLOGY, RAPID SCIENCE PUBLISHERS, US, vol. 17, no. 3, 1 June 2005 (2005-06-01), pages 283 - 288, XP009091242, ISSN: 1040-872X
DESAI NINA N ET AL: "Morphological evaluation of human embryos and derivation of an embryo quality scoring system specific for day 3 embryos: A preliminary study", HUMAN REPRODUCTION (OXFORD), vol. 15, no. 10, October 2000 (2000-10-01), pages 2190 - 2196, XP002481224, ISSN: 0268-1161
ANONYMOUS: "Logistic regression", WIKIPEDIA, THE FREE ENCYCLOPEDIA, 6 March 2007 (2007-03-06), XP002481225, Retrieved from the Internet [retrieved on 20080522]
BOOTH PAUL J ET AL: "Prediction of porcine blastocyst formation using morphological, kinetic, and amino acid depletion and appearance criteria determined during the early cleavage of in vitro-produced embryos", BIOLOGY OF REPRODUCTION, vol. 77, no. 5, November 2007 (2007-11-01), pages 765 - 779, XP008091729, ISSN: 0006-3363
STOKES ET AL: "Development of porcine embryos in vivo and in vitro; evidence for embryo 'cross talk' in vitro", DEVELOPMENTAL BIOLOGY, ACADEMIC PRESS, NEW YORK, NY, US, vol. 284, no. 1, 1 August 2005 (2005-08-01), pages 62 - 71, XP005001694, ISSN: 0012-1606
DETER R L: "Quantitative morphological analysis of early mouse embryogenesis in vitro. I. Perfusion culture system, tissue preparation, sampling.", JOURNAL OF EMBRYOLOGY AND EXPERIMENTAL MORPHOLOGY AUG 1977, vol. 40, August 1977 (1977-08-01), pages 91 - 100, XP008091766, ISSN: 0022-0752
THOMPSON ET AL: "Culture without the petri-dish", THERIOGENOLOGY, LOS ALTOS, CA, US, vol. 67, no. 1, 6 December 2006 (2006-12-06), pages 16 - 20, XP005794536, ISSN: 0093-691X
ANONYMOUS: "Open Mesh Fabrics- Precision Woven Synthetic Monofilament Fabrics", SEFAR CATALOGUE, January 2007 (2007-01-01), XP002481227, Retrieved from the Internet [retrieved on 20080521]
ANONYMOUS: "Open Mesh Fabrics- Precision Woven Synthetic Monofilament Fabrics", SEFAR CATALOGUE ENGLISH, March 2008 (2008-03-01), XP002481228, Retrieved from the Internet [retrieved on 20080521]
Attorney, Agent or Firm:
WARD, Siobhan (40-43 Chancery Lane, London WC2A 1JA, GB)
Download PDF:
Claims:
CLAIMS

1. A method of assessing the developmental potential of an embryo comprising:

(i) incubating the embryo in a culture medium comprising a plurality of amino acids; (ii) determining a change in concentration of at least one amino acid in the culture medium;

(iii) measuring at least one quantifiable morphological and/or kinetic marker; (iv) using the data obtained from step (ii) and step (iii) to obtain an assessment of the developmental potential of an embryo.

2. A method according to Claim 1 wherein the data obtained from step (ii) and step (iii) is used to generate a probability value and wherein a probability value of from 0 to 1 is indicative of an embryo's developmental potential.

3. A method according to Claim 1 or Claim 2 further comprising the step of selecting the embryo according to the assessment of developmental potential.

4. A method according to any of the preceding Claims wherein the assessment of embryo developmental potential is (i) at least 80% accurate, (ii) at least 75% accurate, (iii) at least 70% accurate, (iv) at least 65% accurate.

5. A method according to any of the preceding Claims, wherein the morphological marker is selected from the group consisting of: (i) blastomere number, (ii) evenness of division and (iii) degree of fragmentation.

6. A method according to any of the preceding Claims, wherein the kinetic marker is time of cleavage.

7. A method according to any of the preceding Claims wherein at least one quantifiable morphological and/or kinetic marker is measured on at least one of day one, day two, day three, day four or day five post fertilisation.

8. A method according to any of the preceding Claims wherein the change in concentration of at least one amino acid in the culture medium is determined on at least one of day one, day two, day three, day four or day five post fertilisation.

9. A method according to Claim 7 or Claim 8 wherein data obtained on any one day, or between any two days, from day one to day four is used to obtain an indicator of embryo developmental potential.

10. A method according to any of the preceding Claims wherein a change in concentration of a group of amino acids, typically comprising two to seven amino acids is used to obtain an assessment of embryo developmental potential.

11. A method according to any of the preceding Claims wherein the embryo is derived from any organism including humans, cows, pigs, sheep, any domestic animal or a rare and threatened species.

12. A method according to any of the preceding Claims wherein the assessment of developmental potential is carried out using the formula:

1

\+e z wherein e = base of natural logarithm, 2.718 and z = The sum and/or product of a Constant, a Kinetic Marker(s), an Amino Acid Marker(s), a Morphological Markers) and the possible interactions of any of these markers between themselves at any one or more sampling/observation times,

and wherein the Amino Acid Marker is the concentration or change in the concentration (or quantity or ratio) of one amino acid or a set of amino acids, or a value (i.e. score, index or component) derived from their amalgamation (including that of nitrogen equivalents contained therein).

13. A method according to any of the preceding Claims wherein the embryo is incubated as part of a culture system comprising a plurality of embryos, and each embryo of the system is cultured in a spaced relationship and in chemical communication with other embryos of the system.

14. A method according to Claim 13 wherein the culture system comprises a plurality of incubation chambers, each chamber constructed and arranged to house a single embryo and allow chemical communication between different embryos of the system.

15. A method according to Claim 14 wherein the plurality of chambers are provided by a monofilament woven polyester mesh.

16. A method according to any of Claims 13 to 15 wherein each embryo of the system is positioned at a predetermined distance from a neighbouring embryo.

17. A method according to Claim 16 wherein the predetermined distance is from 80 to 90 μm.

18. A system comprising means for holding embryos in spatial relationship with one another and in communication with the same body of incubation medium.

19. A system according to Claim 18, further comprising means for sampling the incubation medium.

20. A system according to Claim 19, further comprising means for determining a change in concentration of at least one amino acid in the incubation medium.

21. A system according to any of Claims 18 to 20, wherein the means for holding embryos in spatial relationship is a plurality of incubation chambers, each chamber constructed and arranged to house a single embryo and allow chemical communication between different embryos of the system and preferably wherein the plurality of chambers are provided by a monofilament woven polyester mesh.

Description:

ASSESSMENT METHOD

This invention relates to a method of assessing the developmental potential of an embryo.

The ability to predict reliably and non-invasively which early embryos have the ability to develop to full-term would constitute a major breakthrough in embryo-based biotechnologies. Such an ability would not only virtually eliminate multiple pregnancies following human assisted conception and the associated high rates of morbidity and mortality [1], but could, in a major way, benefit domestic animal embryology by reducing non-return rates and allowing predictive parameters to be used as criteria for the selection of superior culture media. Early identification of embryos exhibiting signs of continuing viability would also obviate the need for extended periods of in vitro culture that are associated with a gradual reduction in developmental capacity [2] and disruption of genetic and epigenetic constitution [3].

Since the early days of human IVF [4] and the in vitro production of cattle embryos [5], a positive correlation has been recognised between the speed of early embryo development and subsequent viability, although the earliest cleaving embryos are not always those possessing the greatest developmental capacity [6, 7]. Relationships between embryo cytokinetics and viability have also been established in the hamster [8], rhesus monkey [9] and mouse [7]. In addition to kinetic parameters, other easily quantifiable prognostic markers include the symmetry of cell division and the extent of cytoplasmic fragmentation [10]; indeed, these factors, in association with blastomere number, are

commonly used in human fertility clinics as indicators of developmental potential [H]. With an increasing number of predictive factors available to grade embryos, it became evident that rationalisation of these parameters into a single developmental potential score for individual human embryos was necessary [12, 13]. The concept of a developmental potential index has subsequently been developed into more sophisticated scoring strategies whereby further determinants of developmental potential are incorporated such as pronuclear number and morphology, multinucleation and cytoplasmic granularity [14, 15]. Additional factors that may contribute to the selection of superior embryos include the number, size and alignment of nuclear precursor bodies [16, 17], size and degree of polar body fragmentation [18] embryonic axis deviation [19] and spindle presence [20]. Correlates of developmental potential are not limited to morphological characteristics since prognostic markers can also include embryonic metabolism or the release of growth factors [21, 22]. One particular facet of metabolism showing promise in this respect is the quantification of the net rates of amino acid depletion and appearance by the embryo. Application of this technique in early human embryos has established that the release or uptake pattern of particular amino acids correlates with embryo developmental potential in vitro [23] and to pregnancy rates following transfer [24].

The developmental potential score is often constructed quite simply to facilitate both ease of calculation and practicality in busy IVF clinics but lacks robustness. There remains a need for a more reliable prognostic indicator of developmental potential whereby the ability of an embryo to develop into a blastocyst and/or successfully implant following

transfer can be predicted with a greater degree of certainty. A reliable non-invasive embryo scoring system, undertaken during early cleavage, to predict accurately which embryos are either capable of reaching the blastocyst stage or possess full developmental potential would be of considerable benefit for the advancement of embryo-based biotechnologies in domestic animals and assisted conception in humans. This is particularly the case for embryos of domestic animals, specifically those of pigs and cattle, which present special challenges for non-invasive morphological investigation owing to the large amount of cytoplasmic lipid [39] that effectively precludes the observation of nuclei and hinders or prevents the characterisation of cytoplasmic structure, rendering apparently useful markers of developmental potential in human embryos [40] inapplicable to the pig and cow [41].

The purpose of being able to predict blastocyst formation is dependent on the intended application: in some situations it might be crucial to isolate only those single or groups of embryos that possess full-term viability e.g. for embryo transfer in monotocous species or for research purposes such as gene expression studies. Alternatively, there may be an intention to maximise the percentage of blastocysts correctly classified as a proportion of those predicted while optimising the percentage of embryos correctly classified as blastocysts.

STATEMENTS OF THE INVENTION

According to the present invention there is a method of assessing the developmental potential of an embryo comprising:

(i) incubating the embryo in a culture medium comprising a plurality of amino acids; (ii) determining a change in concentration of at least one amino acid in the culture medium;

(iii) measuring at least one quantifiable morphological and/or kinetic marker; (iv) using the data obtained from step (ii) and step (iii) to assess the developmental potential of an embryo.

The invention provides a simple, but accurate, model of preimplantation development of an embryo by identifying the contributory weighting of certain non-invasive markers to developmental success. Accordingly, the invention provides a prognostic indicator of blastocyst formation, based on the contribution of a number of non-invasive factors which influence developmental capability of an embryo.

The inventors of the present invention have observed a relationship between specific morphological, kinetic and metabolic data, which is, especially when measured sequentially, surprisingly synergistic and can thus be used to provide a more reliable prognostic indicator of embryo developmental potential. The invention is concerned with the principle of using amino acid profiling to provide additional predictive power in the

selection of viable embryos. In one embodiment of the invention, the data obtained in steps (ii) and (iii) of the method is combined to generate a probability value. In a further embodiment of the invention, a probability value of from 0 to 1 is indicative of developmental potential.

The term 'developmental potential' is used in its broadest sense and includes either the demise or degeneration of an embryo prior to the blastocyst stage or the ability of an embryo to develop to blastocyst stage and/or be successfully implanted and/or capable of full-term gestational development.

The method of the invention provides an assessment of embryo developmental potential that is (i) at least 80% accurate, (ii) at least 75% accurate, (iii) at least 70% accurate, (iv) at least 65% accurate. Preferably the method of the invention is 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% accurate.

The method of the invention provides an overall correct classification rate for prediction of blastocyst formation that is at least 30% greater than expected by chance, preferably 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 52, 54, 55, 56, 57, 58, 59 or 60% greater than chance.

Preferably, the addition of the amino acid data to the model raises the number of correctly identified blastocysts by at least 5%, at least 10%, at least 11, 12, 13, 14, 15, 16, 17, 18, 19, 20% over that obtained using morphoplogical and/or kinetic variates alone.

The embryo may be a pre-implantation embryo derived from any organism including humans, cows, pigs, sheep, any domestic animal, any mammal or a rare or threatened species. In one embodiment of the invention the embryo is made by nuclear transfer. In an alternative embodiment of the invention, the embryo is a mammalian pre-implantation embryo and produced by in-vtvo or in-vitro fertilisation or by intra-cytoplasmic sperm injection (ICSI) or parthenogenetic activation.

In one embodiment of the invention, an increase and/or decrease in concentration of at least one amino acid in the culture medium as compared to pre-culture medium is used to determine amino acid turnover. In one embodiment of the invention, a change in concentration of a particular subset of amino acids is used to obtain an assessment of embryo developmental potential. The amino acid turnover of the subset or group of amino acids may be indicative of the ability of the embryo to develop to the blastocyst stage and/or be successfully implanted for that species. In one particular embodiment this subset comprises one or more of the following amino acids: threonine, valine, lysine and phenylalanine and, furthermore, the species is a pig. In an alternative embodiment, the change in concentration of any one, or any combination of the following amino acids is used to obtain an assessment of embryo developmental potential: alanine, cysteine, aspartic acid, glutamic acid, phenylalanine, glycine, histidine, isoleucine, lysine, leucine,

methionine, asparagine, proline, glutamine, arginine, serine, threonine, valine, tryptophan or tyrosine.

The term 'quantifiable marker' is used to define any parameter which can be used to assess or indicate the physiological status of an embryo and which is susceptible of measurement. A 'morphological marker' is a parameter which relates to the form and/or structure of an embryo. A 'kinetic marker' is a parameter concerned with the rate of biochemical reactions of, or relating to, an embryo and rate of development.

Preferably, the morphological marker is selected from the group consisting of: blastomere number, symmetry or evenness of division and degree of fragmentation.

Preferably the kinetic marker is cinematographic. Most preferably the kinetic marker is time of cleavage, the interval between insemination, ICSI, parthenogenetic activation or embryo reconstruction during nuclear transfer and a cleavage event, or the interval between any two cleavage events.

In one embodiment, the method further comprises the step of selecting the embryo according to the assessment of viability. Preferably the selected embryo has increased possibility of development to the blastocyst stage and/or successful implantation. A selected pre-implantation embryo may be introduced into the uterine tract of an organism or mammal. Alternatively, an embryo that is selected for further development may be used in the production of a non-human transgenic organism with desirable qualities such

as disease resistance, high lean mass and capacity to produce human medical products in body fluids (i.e., milk, blood, urine) and/or tissues.

In another embodiment of the invention, the method is used to assess the ability of a pre- implantation embryo to implant and give rise to clinical pregnancy.

Preferably at least one quantifiable morphological and/or kinetic marker is measured at day one, day two, day three, day four or day five post fertilisation, or any combination thereof. In one embodiment of the invention at least one quantifiable morphological and/or kinetic marker is measured at any time from day one to day two post fertilisation and/or from day two to day three post fertilisation, hi one embodiment of the invention data from sequential days are used to obtain an indicator of embryo developmental potential. In a preferred embodiment, day one and day two data are used to obtain an indicator of embryo developmental potential.

In one embodiment of the invention the change in concentration of at least one amino acid in the culture medium is determined at day one, day two, day three, day four or day five post fertilisation, or any combination thereof. In one embodiment of the invention the change in concentration of at least one amino acid in the culture medium is determined at any time from day one to day two post fertilisation and/or from day two to day three post fertilisation. In one embodiment of the invention data from sequential days is used to obtain an indicator of embryo developmental potential, hi another embodiment of the invention the change in concentration of at ' least one amino acid as

determined on day one and day two post fertilisation is used to obtain an indicator of embryo developmental potential.

Preferably the assessment of embryo developmental potential is determined by the mathematical incorporation of markers (preferably non-invasive) of embryo development/viability into a formula. Preferably the developmental potential is measured as or represented by the sum and/or product of a "Kinetic Markers)", a "Metabolic Markers)", a "Morphological Markers)" and the possible interactions of any of these markers between themselves at any one or more sampling/observation times.

Preferably the Kinetic Marker(s) is cinematographic. Most preferably the kinetic marker is time of cleavage, the interval between insemination, ICSI, parthenogenetic activation or embryo reconstruction during nuclear transfer and a cleavage event, or the interval between any two cleavage events.

Preferably the Metabolic Marker(s) is the concentration or change in the concentration (or quantity or ratio) of a substrate, amino acid, hormone, cytokine, chemical, or a set of these, or a value (i.e. score, index or component) derived from their amalgamation.

Preferably the Morphological Marker(s) is blastomere number, symmetry or evenness of division, degree of fragmentation, embryonic axis deviation, oocyte/blastomere volume or diameter, or a morphological feature(s) pertaining to the cumulus cells, the pronuclei (i.e. number, size, or number or orientation of nuclear precursor bodies), multinucleation, the cytoplasm (i.e. granularity, darkness, homogeneity, or rotation), the spindle (i.e.

presence, orientation, quality), the polar body (i.e. degree of fragmentation or orientation), or the zona pellucida (i.e. thickness, diameter or shape), or a set of these, or a value derived from their amalgamation.

Preferably the assessment of embryo developmental potential is made according to the formula:

1

where e = base of natural logarithm, 2.718

and z = The sum of a Constant, a "Kinetic Marker(s)", an "Amino Acid Marker(s)", a "Morphological Markers)" and the possible interactions of any of these markers between themselves at any one or more sampling/observation times.

Preferably the Kinetic Marker is cinematographic. Most preferably the kinetic marker is time of cleavage, the interval between insemination, ICSI, parthenogenetic activation or embryo reconstruction during nuclear transfer and a cleavage event, or the interval between any two cleavage events.

Preferably the Amino Acid Marker is the concentration or change in the concentration (or quantity or ratio) of one amino acid or a set of amino acids, or a value (i.e. score, index or component) derived from their amalgamation (including that of nitrogen equivalents contained therein).

Preferably the Morphological Marker is selected from the group consisting of: blastomere number, symmetry or evenness of division and degree of fragmentation.

Preferably the assessment of embryo developmental potential, namely the probability estimate, is made according to the formula:

1

1+er* where e = base of natural logarithm, 2.718 and z = ±a

±b[cleavage time]

±c[amino acid score]

±d[(Day 1 @2cell)*(Day2@4cell)]

±e[(Dayl@2cell)*(Evenness of division on Day l)*(Day2@3cell)]

±fftTDay 1 @4cell)*(Day2@4cell)]

±g[(Day2@2cell)*(Evenness of division on Day 2)]

±h[(Day2@4cell)*(Evenness of division on Day 2)*(Degree of fragmentation on

Day 2)] where a-h are constants derived from the regression.

Alternatively:

1+erz where e = base of natural logarithm, 2.718 and z = ±a

±b[cleavage time]

±c[amino acid score]

±d[(x blastomeres on Day A)*(y blastomeres on Day B)]

±e[(x blastomeres on Day A)* (Evenness of division on Day A)*

(z blastomeres on Day B)]

±f[(y blastomeres on Day A)*(y blastomeres on Day B)] ±g[(x blastomeres on Day B)* (Evenness of division on Day B)] ±h[(y blastomeres on Day B)*(Evenness of division on Day B)* (Degree of fragmentation on Day B)] where a-h are constants derived from the regression.

Preferably the assessment of embryo developmental potential, namely the probability estimate, is made according to the formula: 1 l+e' z where e = base of natural logarithm, 2.718 andz = +0.501(+0.666)

-0.159(±0.061)[cleavage time]

-0.727(±0.162)[amino acid score]

+1.712(±0.517)[(Day 1 @2cell)*(Day2@4cell)]

-0.365(+0.176)[(Dayl@2cell)*(Evenness of division on Day l)*(Day2@3cell)]

+1.667(±0.804)[(Day 1 @4cell)*(Day2@4cell)]

-0.694(±0.221)[(Day2@2cell)*(Evenness of division on Day 2)]

-0.204(±0.114)[(Day2@4cell)*(Evenness of division on Day 2)*(Degree of fragmentation on Day 2)]

(Where blastomere numbers of embryos on Day 1 and 2 were converted to variables (such variables commonly known as 'dummy variables in the art) using the following coding scheme:

Where Dayl@2cell (1 if 2-cell, 0 otherwise), Dayl@3-cell (1 if 3 -cell, 0 otherwise) and Dayl@4-cell (1 if 4-cell, 0 otherwise). For Day 2 these variables were nominated Day2@2-cell, Day2@3-cell and Day2@4-cell. Where 'cleavage time' is the time interval between insemination and the time of the first observed cleavage).

In one embodiment of the invention the method is automated and the morphological and/or kinetic and/or metabolic markers are provided as computerised morphometric, kinetic or metabolic measurements.

The gradual reduction in developmental capacity and disruption of genetic and epigenetic constitution associated with in vitro cell culture is well documented [2, 3]. There is a need to improve in vitro culture conditions such that maximal blastocyst formation is achieved, thus offering the embryologist maximum choice in selection for transfer.

The benefits of group culture of embryos whereby maximal blastocyst formation is achieved when neighbouring embryos can communicate with each other by way of autocrine/paracrine growth factors is known [25]. However, since the main focus is often upon tracking individual embryos throughout in vitro development and identifying and selecting the optimal embryo for transfer, group culture of embryos is not feasible.

In one embodiment of the invention an embryo is incubated as part of a culture system comprising a plurality of embryos, wherein each embryo of the system is cultured in a spaced relationship and in chemical communication with other embryos of the system.

The term 'chemical' is used in its broadest sense and includes any substance (which may be an element or compound) which is used in producing a biochemical effect. The term includes beneficial factors which stimulate or enhance embryo growth and development, such as paracrine/autocrine growth factors.

Preferably the culture system comprises a plurality of incubation chambers, each chamber constructed and arranged to house a single embryo and allow chemical communication between different embryos of the system. In one embodiment of the invention, the

incubation chambers comprise a porous material. Most preferably the plurality of chambers are provided by a monofilament woven polyester mesh.

Preferably the woven polyester mesh is composed of monofilaments between which embryos can be placed such that neighbouring embryos are separated by the optimal distance for maximal blastocyst formation. This permits the double benefit of group culture whilst enabling the tracking of individual embryos throughout in vitro development. The mesh system generates blastocyst rates equivalent to those recorded from both traditional group culture and the "well of the well" (WOW) system [86].

Preferably each embryo of the system is positioned at a predetermined distance from a neighbouring embryo. Preferably the predetermined distance is from 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, μm, preferably 80 to 90 μm. In one embodiment the distance is 84 μm.

The culture system permits localisation and identification of individual embryos throughout in vitro culture whilst retaining the developmental benefit of group culture and inherent paracrine/autocrine growth factor effects. The mesh culture system allows neighbouring embryos to be separated from one another by a distance previously determined to generate maximal blastocyst yields [25].

Accordingly in one embodiment of the invention there is provided a system comprising means for holding embryos in spatial relationship with one another and in communication with the same body of incubation medium.

Preferably the system further comprises means for sampling the incubation medium of an individual embryo. More preferably the system further comprises means for determining a change in concentration of at least one amino acid in the incubation medium, preferably by HPLC.

Accordingly, the present invention also provides a cell culture system comprising a network of selectively permeable chambers, wherein each chamber allows physical separation of a cell from surrounding cells and allows chemical communication between a cultured cell and its environment. Preferably the network comprises a woven polyester mesh composed of monofilaments and a cell to be cultured is placed between the monofilaments of the polyester mesh.

DETAILED DESCRIPTION OF THE INVENTION

The invention will now be described by way of example only and with reference to the following drawing wherein:

Figure 1 shows the embryo scoring system modified from Ziebe et al. [10]. Embryos were evaluated morphologically on Day 1 and Day 2 in terms of number of blastomeres, evenness of division and degree of fragmentation. Scores of 2, 3 and 4 for evenness of division represented differences in diameter between blastomeres of 0-19%, 20-29% and

>30%, respectively. To illustrate the system for scoring evenness of division and degree of fragmentation, this example utilises a 2-cell embryo.

Figure 2 is a photograph of a section of a piece of woven polyester mesh (SefarPetex). In the experiment, embryos were cultured in the mesh from Days 2 to 6 in groups of approximately 16 in 4x4 arrangements. The mesh system permitted identification of individual embryos yet still retained the developmental benefit of group culture and inherent paracrine/autocrine growth factor effects.

Figure 3 is a summary of sequential embryonic development and blastocyst production. Embryos were segregated according to the cell number observed at first cleavage on Day 1 and their subsequent cell number on Day 2. For embryos evaluated on Day 1, the greatest number of blastocysts was generated from 2-cell embryos, although the highest percentage (40.6) was produced by 4-cell embryos. Embryos at the 2-cell stage on Day 1 that subsequently divided to 4-cells by Day 2 yielded the largest number of blastocysts. A small proportion of embryos evaluated on Day 2 possessed fewer blastomeres than on Day 1. Values on Day 1 are blastocysts/number of embryos within each category of cell number (%). Values on Day 2 represent the subsequent distribution of these blastocysts (%) according to the cell numbers of embryos observed on Day 2. Blastocyst rates of embryos that were at the 2, 3, 4 and 5-8 cell stage on Day 2 were 6.4, 2.4, 47.9 and 30.8%, respectively.

Figure 4 shows blastocyst production by 2-cell embryos recovered on Day 1 classified morphologically according to evenness of cell division and degree of fragmentation on

Days 1 and 2, and by cell number on Day 2. On Days 1 and 2 each embryo received a three integer score allocated according to the grading system detailed in Fig. 1. Apart from the initial value (the blastocyst rate of 2-cell embryos: 65/248) the values shown represent the distributions of the embryos from the immediately preceding morphological estimates expressed as blastocysts/number of embryos (%). The sequential morphologies on Days 1 and 2 of the embryos generating the first, second and third highest blastocyst yields are annotated by the bold, dashed and dotted red lines, respectively. These correspond to the sequential three integer embryo scores (on Days 1 and 2) of 2,2,0->4,2,0, 2,3,0→4,3,0 and 2,2,l->4,2,0, respectively.

Figure 5 shows the effect of evenness of division (A, B) and degree of fragmentation (C, D) in cleaved embryos on Day 1 (A, C) and 2 (B, D) on subsequent blastocyst development. The blastocyst yields presented in A and C are for those embryos collected on Day 1 that cleaved (i) to any cell number, (ii) 2-cells only (presumptive cyto- numerically normal embryos), and (iii) >3-cells (presumptive cyto-numerically precocious embryos). Li B and D, the blastocyst yields are given for (i) all classes of cleavage stage on Day 2, and (ii) those embryos that were 2-cell embryos on Day 1 and developed to 4-cell embryos on Day 2 (presumptive cyto-numerically normal embryos), and (iii) those embryos that possessed fewer or more than 4 cells on Day 2 (presumptive cyto-numerically deviant embryos). Number of cleaved embryos evaluated are given on bars.

Figure 6 shows the distribution of embryos in relation to evenness of division (A) and degree of fragmentation (B) (evaluated on Day 1) after separation into fast and slow cleaving embryos. Fast and slow cleaving embryos were those dividing between 21-25 and 27-31 h post insemination, respectively. The ordinate axis represents embryo numbers within each group expressed as percentages of the total number of fast or slow cleavers. Different distributions (P<0.01) of embryos are observed between fast and slow cleaving embryos for evenness of division and degree of fragmentation: the quality of slow cleaving embryos in terms of both of these morphological parameters is inferior compared to those cleaving by 25 h post insemination i.e. the distributions are shifted to the right.

Figure 7 shows net rates of amino acid appearance and depletion in Day 1 embryos that developed to blastocysts and those that arrested/degenerated before reaching this stage. The net rates of appearance of glycine, isoleucine, valine and lysine, and the net depletion rate of threonine were significantly different between groups. All net rates were significantly different (P<0.05) from zero.

Figure 8 shows total net amino acid appearance, depletion, balance and turnover in Day 1 embryos that either subsequently developed to blastocysts or arrested/degenerated prior to the blastocyst stage. Total amino depletion (P=0.0086) and balance (P=0.0432) were significantly different between the two groups. All net rates were significantly different (PO.001) from zero.

Figure 9 shows the distribution of blastocysts and degenerate embryos in relation to their predicted probability values generated by the logistic regression model. The dashed line represents a probability level of 0.5, above and below which embryos are predicted to develop to blastocysts or to degenerate/arrest, respectively.

Figure 10 shows the relationships between the cutoff point of probability value above which embryos could be selected and the percentages of a) blastocysts correctly predicted of observed (i.e. percentage of blastocysts remaining of total originally available), b) degenerate embryos correctly predicted of observed and, c) blastocysts of predicted. The data was generated from the full logistic regression model. The figure suggests that selection of a probability value of greater than 0.5 has little effect on the percentage of blastocysts of predicted but that raising the cutoff threshold beyond this point reduces the percentage of blastocyst remaining. Homogeneity of the selected sample is practically impossible since only embryos possessing probability values of 0.9 will be all become blastocysts, at which level only 2.4% of the blastocysts available would be selected for use. The optimum probability level for selection would appear to be 0.5 (dashed line) at which 80.8% of selected embryos would be predicted to become blastocysts representing 51.2% of the blastocyst population available.

Figure 11 shows Receiver operating characteristic (ROC) curve of the fitted logistic regression equation representing the probability of true positive results as a fixnction of those that are false positive. The diagonal reference line represents a ROC curve equivalent to chance. The area under the curve is 0.839 (P<0.003) and represents a global

measure of predictive accuracy. The point at which the sensitivity and specificity are maximal is encircled.

MATERIALS AND METHODS

Embryo production

Cumulus-oocyte complexes (COCs) were aspirated from 2-6 mm diameter follicles from slaughterhouse-derived ovaries taken from pre-pubertal pigs. The COCs were selected for the presence of an intact and compact cumulus investment several cellular layers deep and a homogenous ooplasm. They were matured in groups of 50 in 100 μL TCM-199 supplemented with 0.1% (w/v) PVA, 2.8 mM glucose, 0.68 mM glutamine, 0.91 mM pyruvate, 0.57 mM cysteine, 10 ngmF murine epidermal growth factor, 0.5 μg ml 1 FSH and 0.5 μg ml" 1 LH. After 44 h IVM, COCs were washed (x3) with mTBM [26] containing 1.5 mM caffeine and transferred in groups of 35 COCs to 100 μL mTBM. Frozen-thawed semen, kindly provided by GTC Scotland (PIC Sygen, UK), was overlaid on a two-layer (90/45%) Percoll (Pharmacia, Uppsala, Sweden) gradient. After centrifugation at 700 g for 30 min, the pellet was resuspended in 4 mL mTBM. Following re-centrifugation at 350 g for 5 min, the pellet was diluted in mTBM and used to inseminate the oocytes at a final concentration of 6xlO 4 spermatozoa ml" 1 . The day of fertilisation was regarded as Day 0. Six hours after insemination, cumulus cells from the presumptive zygotes were removed by vortexing in modified NCSU-23 [27] designated NCSU-23^. The NCSU-23^ medium contained 20 amino acids [28], the concentrations of which were based on those measured in tubal fluid produced during vascular perfusion of the human Fallopian tube using Medium 199 supplemented with 4% BSA [29].

Embryos were then washed (x2) in fresh medium before being placed in groups of 20 in 2OpL NCSU-IS 33 .

On Day 1, at 21, 23, 25, 27, 29 and 31 h post-insemination, embryos that had cleaved to the 2-cell stage, plus those that had divided into 3-cells or even attained the 4- or 5-8 cell stage between the 2 h observation time-points, were removed from the culture dishes. These embryos were washed (x5) in 100 μL drops of NCSU-23^ before being transferred individually in a narrow-bore glass capillary (approximately equivalent to the embryos' diameter) in a minimal volume to 1.5 μL drops Of NCSU^S 33 under oil for the 24 h amino acid profiling procedure. The glutamine concentration in the NCSU-23^ in the drops during this 24 h incubation period was reduced to 0.2 mM in order to improve the sensitivity of detection of this amino acid by HPLC. Prior to amino acid profiling, the embryos were evaluated morphologically in terms of i) number of blastomeres, ii) evenness of division and iii) degree of fragmentation, so that each embryo received a three integer code according to a scoring scheme (Fig. 1) modified from Ziebe et al., [10]. For example, an evenly cleaved 2-cell embryo with no fragmentation received a score of 2,2,0 while a 4-cell embryo with slightly uneven cleaved blastomeres and approximately 15% fragmentation was scored as 4,3,2. The term cyto-numerically deviant was applied to embryos that did not conform to the pattern of cleavage that is believed to represent normality i.e. porcine embryos would be expected to cleave to 2-cells on Day 1 and be at the 4-cell stage by Day 2 [30, 31].

After 24 h (Day 2), the medium within the drop was gently mixed and the embryo removed in a narrow-bore glass capillary in a similar manner as described for its addition in order to minimize volume changes. Control 1.5 μL drops were located alongside those containing the embryos to control for non-specific changes in amino acid depletion and appearance during the incubation and sample storage periods (e.g. the breakdown of amino acids to ammonium). The drop dishes were frozen at -80°C until amino acid analysis by HPLC. Immediately prior to recovery from the 1.5 μL drops, embryos were re-evaluated in terms of the three morphological criteria (Fig. 1) such that each embryo ultimately received two embryo scores in terms of three integers; one before (Day 1) and one immediately at the end of the 24 h incubation period (Day 2).

Culture and localization of individual porcine embryos

Recovered embryos were placed individually between the filaments of a piece (approximately 2 mm x 2 mm) of non-toxic woven polyester mesh (SefarPetex; Code 07- 160/43; Sefar, Switzerland) in a grid fashion in groups of approximately 16 in 20 μl NCSlK^aa (Fig. 2). This novel system allowed identification of individual embryos and permitted an equivalent rate of blastocyst development compared to our conventional culture system of growing embryos in groups of 20 in 20 μl medium. The size of the mesh opening (160 μm) was sufficient for embryos to lie snugly between the filaments while the filament diameter (84 μm) was within the optimal distance (81-160 μm) for neighboring embryos to benefit from autocrine/paracrine growth effects [25]. On Day 6, embryos were classified according to whether they had developed to the blastocyst stage or had degenerated.

All chemicals were supplied by Sigma Chemical Co. (St. Louis, MO, USA) unless otherwise stated. IVM, IVF and IVC were all performed in pre-equilibrated drops of media under mineral oil in a humidified atmosphere of 5% CO 2 in air at 39°C in petri dishes (Falcon, Becton Dickinson, NJ, USA).

Polyspermy analysis

An estimate of the degree of polyspermia was carried out 12 h after the beginning of IVF in -35 zygotes/replicate. Zygotes were fixed in acetic acidrethanol (1:3) under coverslips for 5 d, stained with 1% (wt/vol) orcein and observed under a phase contrast microscope.

Analysis of amino acid depletion and appearance

From each 1.5 μL drop, 1.2 μL was removed and diluted in 23.8 μL purified water (ELGA Purelab; Elga, UK) in HPLC tubes. Any variations in pipetting during sample recovery were annulled by mathematical correction in relation to the assayed amount of the non-metabolizable amino acid D-α-amino-n-butyric acid that was supplemented to the NCSU-23^ (Table 1).

A reverse-phase HPLC analytical technique was employed, as previously described [32], with minor changes. Briefly, the amino acids were derivatized to fluorescent products by automated reaction of the sample with an equal volume of o-phthaldialdehyde (OPA) containing 2 μL.ml 1 2-mercaptoethanol. The HPLC system was a Waters 2695 Alliance linked to a Waters 2475 fluorescence detector. The flow rate through the column, a

Phenomenex Gemini 5 μm (4.6x100mm) (Phenomenex, Cheshire, UK) was 1.3 ml.mhr 1 with the column temperature controlled at 35 0 C. The two solvents required to generate the elution gradient were a 1:4 and 4:1 (v/v) ratio of methanoksodium acetate (83 mM, pH 5.9).

The chemistry of the HPLC method did not permit the detection of cysteine and proline and consequently 18 amino acids were measurable using this technique. Furthermore, due to their very high concentrations in NCSU-23, taurine (7 mM) and hypotaurine (5 mM) exceeded the upper detectable limit of the assay.

Statistical analyses

All means are presented as ±SEM and differences between groups were assumed to be significantly different at a level of P<0.05, unless stated otherwise. Normality of the data sets were evaluated by the Kolmogorov-Smirnov test. MulticoUinearity was also investigated; any tolerance values <0.2 were identified and any condition indices >15 were examined followed by comparison of coefficient decomposition between variables.

Blastocyst rates between groups were analyzed by X tests. The statistical analyses were performed using SPSS.

Amino acids

The net rates of amino acid or nitrogen appearance and depletion were calculated as pmol/embryo/h. It should be appreciated that net rates of amino acid depletion and appearance represent the difference in absolute rates of uptake and release which,

theoretically, could greatly exceed the net rates of depletion and appearance being observed.

Net rates of nitrogen appearance and depletion were determined by multiplying amino acid net rates of appearance or depletion by the number of nitrogen atoms contained in the respective amino acids [28]; i.e. four atoms of nitrogen in arginine, three in histidine, two in tryptophan, asparagine, glutamine and lysine, and one in the remaining amino acids.

In each group of embryos, total net amino acid appearance and total net amino acid depletion were calculated as the sum of the net rates of all those amino acids being released and disappearing, respectively. Additionally, total amino acid balance and total amino acid turnover represented the difference between, and sum of, the total net amino acid appearance and depletion, respectively. Rates of total nitrogen appearance, depletion, balance and turnover were calculated in a corresponding manner. It should be recognized that the 'total' rates calculated here are underestimates of the true rates of total amino acid and nitrogen depletion and appearance since i) cysteine and proline were not measured, and ii) amino acids may be released intracellularly from endocytosed bovine serum albumen contained in the medium [33, 34].

In those treatments containing embryo groups in which the complete set of 18 amino acids could not be measured, replicate sizes of treatments were reduced during the calculation of total amino acid and nitrogen appearance, depletion, balance and turnover.

Those sets conforming to the null hypothesis were analyzed by one-way analysis of variance (ANOVA). Significance (i.e. PO.05) was investigated by the Fisher least squares difference test. Non-parametric data sets were analyzed by the Mann- Whitney U test. The effect of time of first cleavage on blastocyst rates was analyzed by logistic regression. Differences from zero in the rates of appearance, depletion, balance and turnover of amino acids or nitrogen were determined by the Wilcoxon signed ranks test.

Discriminant analysis

Discriminant analysis was applied to the amino acid data to maximize the variance between a priori defined groups and to isolate a subset of amino acids that, in combination, provided the greatest discrimination. The assumption of equal covariance between groups was checked by Box's M test while any violations of multivariate normality were corrected by appropriate transformation of the data. The discriminant function was derived by both stepwise estimation using Mahalanobis D 2 measures and simultaneous estimation. Structure matrix loadings of approximately ±0.3 or greater were considered significant unless coUinearity between any such variables reduced the discriminatory power [35]. Discriminatory scores derived by the selected function were included as an independent variable in the logistic regression.

Logistic Regression

Determination of the degree by which variables measured during early cleavage could be predictive of blastocyst development was analyzed by logistic regression [36]. The dichotomous dependent variable registered (i.e. blastocyst formation or degeneration)

was coded as 1 (for blastocyst development) or 0 (for arrested development/degeneration). The independent variable predictors registered on Days 1 and 2 were blastomere number, evenness of division and degree of fragmentation. Time of first cleavage and discriminant analysis amino acid score were also entered as independent variables. Ordinal coding for evenness of division is detailed in Fig. 1. Coding for degree of fragmentation for the logistic regression was altered from 0, 1 and 2 (see Fig. 1.) to 1, 2 and 3, respectively. The interval scale for the time of cleavage post insemination was applied unaltered. Dummy variables [37] were created for the three categories of blastomere number; the names of the dummy variables and their coding were as follows: Dayl@2cell (1 if 2-cell, 0 otherwise), Dayl@3-cell (1 if 3-cell, 0 otherwise) and Dayl@4-cell (1 if 4-cell, 0 otherwise). According to this categorization system, 5-8 cell embryos would be coded 0. Blastomere numbers of embryos on Day 2 were also converted to dummy variables using the identical coding scheme. These variables were nominated Day2@2-cell, Day2@3-cell and Day2@4-cell.

Inclusion of predictor variables in the fitted models were achieved by both forward and backward stepwise logistic regression plus judicial selection or elimination of variables (vide infra). The level of significance defined as a threshold for inclusion was reduced from P<0.05 to the more liberal P≤O.l to avoid exclusion of potentially important variables [38]. Only variables and interaction terms were tested that were of biological interest and validity or that were intuitively plausible from literature on embryology. This restriction was necessary to avoid allowing random sampling variation to generate idiosyncratic models, and to prevent overfitting. Two- and three-way interaction terms

were introduced into the equation to generate a hierarchically well-formulated model [37]. Models were selected on the basis of their predictive accuracy, parsimony and goodness of fit tests (the Hosmer-Lemeshow test and pseudo R 2 statistic) on the assumption that the former two aspects took precedence over the latter tests [36]. The pseudo R 2 value is a measure of the variance explained by the predictor variables and varies between 1, for a model that perfectly predicts the outcome, to 0 in which the variables chosen are of no value. Measures of predictive efficiency of the models were presented as the percentage of embryos correctly classified overall, the percentage of blastocysts categorized as a proportion of the number predicted, and the added value (also known as Goodman and Kruskal's λ) of the model. The latter is the percentage of correctly classified embryos beyond the number that could be correctly predicted simply by choosing the category of the largest size i.e. since degenerate embryos represent ~74% (depending on the model) of all embryos, chance alone can achieve this same level of predictive accuracy.

Outlying observations were identified as those possessing extreme Studendized residuals, leverage and Dfbeta coefficient values which exceeded the limits suggested by Hair et al. [35]. Outliers were only removed if they possessed a combination of these values that were extraordinary, thereby suggesting that they were not representative of the group but exerted a disproportionate impact on the model. Due caution was taken to limit the number of outliers eliminated from the data set and to avoid the deletion of those that could not be accommodated by the model owing to any inadequacies of the predictor variables.

RESULTS

Fertilisation and Polyspermy Rates

Orcein staining of samples of zygotes 12 h after insemination indicated that the penetration rate, the percentage of polyspermic oocytes and the number of spermatozoa per penetrated oocyte were 55.7±6.6%, 27.4±8.7% and 1.4±0.2%, respectively.

Blastocyst development

Five replicate experiments were undertaken using a total of 356 embryos of which 28.70+6.19% developed into blastocysts. The cleaved embryos recovered on Day 1 were at the 2, 3, 4 and 5-8 cell stage of development. Since all cleaved embryos were removed at 2 h intervals, those embryos recovered at the 4 and 5-8 cell stage had divided rapidly from 1 cell zygotes within these 2 h periods. The progressive development of cleaved embryos between Day 1 and 2 is depicted in Fig. 3. The blastocyst rates of embryos isolated on Day 1 at the 2, 3, 4 or 5-8 cell stage were 27.9, 26.7, 40.6 and 16.1%, respectively, and were not significantly different. However, significantly different (P<0.001) blastocyst rates were produced from embryos that were at the 2-cell (6.4%), 3- cell (2.4%), 4-cell (47.9%) and 5-8 cell stage (30.8%) on Day 2. Two-cell embryos collected on Day 1 produced the greatest number of blastocysts (65 blastocysts; 27.9%) although 4-cell embryos isolated on the same day generated the highest percentage of blastocysts (40.6%). The state of development of embryos on Day 2 that had previously

divided into 2, 3, 4 or 5-8 cells on Day 1, together with the proportion of blastocysts produced at each developmental stage are also shown in Fig. 3. Two-cell embryos on Day 1 that developed into 4-cell embryos on Day 2 produced the greatest number of blastocysts (52.2%) (Fig. 3). It is noteworthy that some embryos that were evaluated morphologically on Day 2 possessed fewer cells than had been previously recorded on Day 1. As 2-cell embryos (on Day 1) generated the greatest number of blastocysts, the morphological characteristics of these developing embryos on both Days 1 and 2, in terms of blastomere numbers, evenness of cleavage and degree of fragmentation are summarized in Fig 4. The data indicate that the sequential scores of embryos developing from Day 1 to Day 2 that produced the first, second and third greatest number of blastocysts were 2,2,0→4,2,0, 2,3,0→4,3,0 and 2,2,l→4,2,0, respectively. The logistic coefficients for the categorical values of cell number (vide infra) were significant on Day 2 (all P<0.02) but not Day 1 when examined individually (Table 3), although none of these variables in isolation could correctly classify any blastocysts (Table 4).

Evenness of division and degree of fragmentation

The relationships between (i) evenness of cellular division, and (ii) degree of fragmentation on Days 1 and 2, and blastocyst yield are illustrated in Fig. 5. On Day 1, three categories of embryo were analyzed for the effects of these morphological parameters: a) all embryos which had cleaved on Day 1 regardless of cell number, b) those embryos which had cleaved to 2-cells (and were tentatively designated as presumptive cyto-numerically normal) and, c) embryos which possessed >2-cells (and could be possibly regarded as presumptive cyto-numerically precocious). Three classes of

embryo were also analyzed on Day 2: a) all embryos, b) those which had cleaved to 2- cells on Day 1 and subsequently developed into 4-cell embryos by Day 2 (presumptive cyto-numerically normal), c) embryos which comprised fewer or more than 4-cells on Day 2 (presumptive cyto-numerically deviant). Examination of the data for evenness of division suggests that the relationship between this morphological parameter of embryo quality and blastocyst yield is not linear: rather, that slight asymmetry of division (score level 3) is not detrimental to blastocyst yield whereas severe asymmetry (score level 4) hindered subsequent development. This relationship was consistent on Days 1 and 2 for all the embryo categories portrayed in Fig. 5 except for embryos of >3 cells on Day 1. In contrast, a linearity in response between degree of fragmentation and blastocyst yield was clearly established in all classes of cleaved embryos on Day 1 (Fig. 5). This relationship was similarly expressed in 4-cell embryos on Day 2 which had developed from 2-cell embryos on Day 1 (presumptive cyto-numerically normal embryos) but was weaker in the group comprising all cleaving embryos on Day 2, and negligible in embryos that possessed <3 or >5 cells on Day 2. Data from all the embryos regarding evenness of cell division and degree of fragmentation were also analyzed by logistic regression. This established that the negative slopes of the individual logistic regression equations were significant for degree of fragmentation on Days 1 and 2 (both PO.01) and for evenness of division on Day 2 (P=0.028) but not Day 1 (Table 3), although none of these parameters by themselves could predict blastocyst development.

Timing of cleavage and blastocyst rate

A inverse relationship was recorded between the timing of the first division of all cleaved embryos and subsequent blastocyst yields (Table 1); a relationship that was similarly apparent on examination of those embryos that had divided to 2-cells only (presumptive cyto-numerically normal) (P<0.001) or to >3 cells (presumptive cyto-numerically deviant embryos) (P=COI l). hi concordance with this relationship, a significant (P<0.001) negative logistic regression coefficient was recorded when this parameter was examined in isolation (Table 3) although this model was inadequate to classify any blastocysts accurately (data not shown). Blastocyst yields at each timepoint expressed as percentages of the total number of blastocysts produced were 23.3±5.4, 33.1±4.2, 25.9+5.6, 9.2±2.1, 7.4±2.9 and 1.2+1.1% at 21, 23, 25, 27, 29 and 31 h post-insemination, respectively. Consequently, 56 and 82% of total blastocyst yields were generated by the second and third collection times i.e. by 23 and 25 h post-insemination, respectively. The number of cleaved embryos at each collection time expressed as percentages of the total number of embryos collected were 12.1, 25.8, 28.7, 15.7, 12.1 and 5.6%, respectively, indicating that the frequency of cleavage was substantially higher after 21 h and up until 25 h post- insemination compared to the periods outside of this range.

The effect of cleavage time on evenness of division and degree of fragmentation was also examined. Embryos were divided into fast and slow cleavers defined by those cleaving in two equal 3 h periods; namely between 21-25 h and between 27-31 h post insemination, respectively. Examination of all embryos on Day 1 (i.e. regardless of whether they subsequently became blastocysts or degenerated) established that the distribution of

embryos according to the three classes of degree of fragmentation and between fast and slow cleavers were significantly different (P<0.01) (Fig. 6B): slower cleaving embryos exhibited greater degrees of fragmentation than those cleaving within 21-25 h post insemination, thereby causing the distribution of such embryos to be shifted to the right in Fig. 6. This difference in distribution between fast and slow cleavers did not exist when the degree of fragmentation was examined on Day 2 (data not shown). However, if only those embryos that developed to blastocysts were included in the analysis, different distributions in degree of fragmentation between fast and slow cleavers were established on Day 1 (P<0.01) and Day 2 (P<0.05) (data not shown) that were similar in profile to Fig 6B. The distributions of embryos in terms of evenness of division between fast and slow cleavers was also investigated. Examination of all embryos (those subsequently developing to blastocysts or degenerating) indicated a difference in distribution in evenness of division between fast and slow cleavers on Day 1 (P<0.01) but not on Day 2 (data not shown). This difference in the distribution was observed as a shift from score 2 to score 3 in slower cleaving embryos thereby representing an increase in asymmetry of division. Examination of only those embryos that developed to blastocysts indicated the lack any of differences in distribution when evenness of division was evaluated on Day 1 and Day 2 (data not shown).

Amino acid analyses

Of 356 amino acid samples analyzed by HPLC, 33 were lost due to technical failures. The net rates of appearance or depletion of amino acids together with the total net rates of appearance, depletion, balance and turnover of amino acids and nitrogen by fast and slow

cleavers are presented in Table 2. All rates were significantly different (P<0.001) from zero. The net rate of appearance of methionine was lower (P<0.001), the net rate of appearance of asparagine was higher (P=0.004) and the net rate of depletion of arginine was greater (P=0.04) in fast compared to slow cleavers. Overall, the total net rates of depletion (P=0.013) and turnover (P=0.027) of amino acids were greater in those embryos cleaving before 25 h post-insemination. Similarly, total net nitrogen depletion (P<0.001) and turnover (P=0.005) were greater in fast cleaving embryos. The greater total net depletion rate of nitrogen by fast cleaving embryos produced a larger balance (P=0.024) in total net nitrogen between these and the slower dividing embryos.

The net rates of appearance or depletion of amino acids between those that developed to blastocysts and those that degenerated or arrested are illustrated in Fig. 7. Embryos that progressed to become blastocysts expressed greater net rates of appearance of glycine (P=0.0228) and depletion of threonine (P<0.001) than those that degenerated. In contrast, lower net rates of isoleucine (P=0.0087), valine (P=0.0322) and lysine (P=0.0402) were recorded in the embryos that achieved blastocyst development compared to those that degenerated. Greater total net rates of amino acid depletion (P=0.0086) were observed in those embryos developing to blastocysts causing a larger total net balance (P=0.0432) in amino acids in these embryos (Fig. 8). Such differences were not reflected in the total net rates of nitrogen depletion (-4.57+0.25 vs. -4.31±0.15) and balance (-1.79+0.13 vs. - 1.52±0.11) nor in appearance (2.78+0.15 vs. 2.79±0.09) or turnover (7.35+0.38 vs. 7.10±0.21) between developing or degenerating embryos, respectively.

Stepwise discriminant analysis identified threonine, valine, isoleucine, lysine, leucine and phenylalanine as possessing high structure matrix loadings. However, isoleucine and leucine were excluded from the function since they exhibited collinearity with the amino acids already included thereby reducing the discriminatory power. The discriminant scores on their own yielded a significant logistic regression (P<0.001) (Table 3) although it could only correctly identify 6.9% of the observed blastocysts (Table 4). Furthermore, the reduction in the percentage of correctly predicted degenerate embryos reduced the added value to below that of chance.

Logistic regression models

In addition to the logistic regression analysis of potential predictor variables examined univariately (Table 3), combinations of variables were selected to determine their predictive accuracy as presented in the classification matrices of Table 4. The use of blastomere numbers on Day 1 or Day 2 or of blastomere numbers on Day 1 in combination with the simultaneous determination of evenness of division and degree of fragmentation were of no value as determinants of subsequent blastocyst formation. Associating blastomere numbers on Day 1 with the time that the embryos cleaved correctly identified 5.4% of blastocysts but simultaneously misclassifϊed 2.3% of the degenerate embryos thereby reducing the success rate of prediction to below that of chance. Incorporating cleavage time and blastomere numbers on Day 1 with both evenness of division and degree of fragmentation on Day 1 did not improve the success rate of prediction indicating that combinations of these three estimates of morphology and cleavage time on Day 1 could not predict blastocyst development. In contrast,

evaluation of morphological parameters on Day 2, in the absence of the cleavage time data, could correctly classify 49.4% of observed blastocysts representing 56.4% of those predicted. Using this model, an 11.2% increase in added value was achieved over chance.

In contrast to the lack of predictive accuracy of utilizing blastomere numbers on Days 1 or 2 in isolation, combining these categorical variables in the logistic regression could successfully identify over 60% of observed blastocysts although the substantial (19.2%) misclassification of degenerate embryos only raised the added value to 4.5% above chance. A more successful model involved adding cleavage time to the cell number data recorded on Days 1 and 2 whereby 63.5% of predicted embryos became blastocysts representing a 19.8% increase in added value. Further incorporation of evenness of division and degree of fragmentation of embryos on Days 1 and 2 into the latter model raised the percentage of blastocysts out of those predicted to 66.2% and the percentage of correctly classified embryos above that attainable by random allocation to 27.3%.

Inclusion of the amino acid scores into the analysis to form the final model again augmented the success rate, such that 80.8% of predicted embryos were correctly classified as blastocysts. Furthermore, 51.2% of observed blastocysts were successfully categorized generating an overall correct classification rate for prediction of both classes of embryo of 84.2% which was 39% greater than the number expected by chance. The variables and interaction terms included in this full model are listed in Table 5. All the logistic coefficients are significant apart from the interaction (P=0.073) between the dummy variable for 4-cell embryos on Day 2, evenness of division on Day 2 and degree of fragmentation on Day 2. This interaction was, however, still included as its presence improved the accuracy of prediction while still maintaining a parsimonious solution [38].

This full model excluded only 7 outlying samples, although inclusion of these outliers in the model only reduced the overall, added value and correctly classified blastocysts of predicted by 1.5, 3.4 and 3.6%, respectively. Owing to the non-linearity of the relationship between blastocyst rate and evenness of division on Days 1 and 2 (see Fig. 5A,B), binary categorical coding was tested to identify any improvements in model fit; in this scenario, embryos scoring 2 and 3 were coded 1, while those scoring 4 were coded 0. For the same reason, low blastocyst numbers generated by embryos scoring 2 for degree of fragmentation on Day 2 (Fig. 5D) also warranted binary categorization of this parameter by combining scores 1 and 2. However, neither of these alterations improved the fit of the models were therefore not incorporated.

The frequency distributions of blastocysts and degenerate embryos in relation to the probabilities predicted by the full logistic regression model are depicted hi Fig. 9. The embryo categories possess two distinct distributions: degenerate embryos exhibit a positive skewness having a median value of 0.11 indicating the reasonable predictive accuracy of this embryo category (95.7%). In contrast, blastocysts exhibit a flat distribution with predicted probabilities ranging from 0.02 to 0.92 (median 0.51) indicative of poor predictive accuracy (51.2%) but, as already stated, is sufficient to correctly identify over 80% of predicted blastocysts. Despite the latter level of accuracy, selection criteria that maximize the numbers of observed blastocysts out of those predicted are relevant for embryo selection purposes. To this end, Fig. 10 suggests that altering the probability threshold beyond which embryos are selected to greater than the normal 0.5 level has little effect on the percentage of observed blastocysts out of those

predicted (see also Fig. 9) because the distribution of both the degenerate embryos and those forming blastocysts are relatively flat between the probability values of 0.5 and 0.85. Moreover, raising the probability threshold merely reduces the number of observed blastocysts in the predicted sample. A homogeneic sample of blastocysts could only be realized using a probability threshold of 0.9 at which level only 2.4% of the total number of observed blastocysts would be isolated.

Receiver operating characteristic (ROC) curve

A ROC curve for the fitted model is depicted in Fig. 11. This shows the fraction of true positive results as a function of those that are false positive. The area under the curve is a global measure of the predictive accuracy of the model which, in this instance, is 0.839 (95% confidence intervals: 0.78-0.89) (P=COOl) which thereby rejects the null hypothesis and suggests that the predictive accuracy of the model is good. The probability value at which the sum of the sensitivity and specificity was maximized was 0.33 corresponding to a sensitivity and 1 -specificity of 0.72 and 0.19, respectively (Fig. 11). Using this probability as a threshold in Fig. 10, the positive predictive value of blastocyst formation and degeneracy are 70.7 and 81.6%, respectively. However, information derived from Fig. 10 suggests that a more pragmatic cutpoint is 0.5 (vide supra).

Probability estimates offiill logistic regression model

Using the full logistic regression model detailed in Table 5, probability estimates of selected combinations of predictor variables were calculated (Table 6) according to the formula below:

1 \+er z

where e = base of natural logarithm, 2.718 and z = +0.501

-0.159[cleavage time]

-0.727[amino acid score]

+1.712[(Dayl@2cell)*(Day2@4cell)]

-0.365[(Dayl@2cell)*(Evenness of division on Day l)*(Day2@3cell)]

+1.667[(Day 1 @4cell)*(Day2@4cell)]

-0.694[(Day2@2cell)*(Evenness of division on Day 2)]

-0.204[(Day2@4cell)*(Evenness of division on Day 2)*(Degree of fragmentation on Day 2)]

Estimated probability values in relation to sequential cell numbers on Days 1 and 2 generally vary in good agreement to those observed (see Fig. 3). Compliance between these estimated probability values is particularly close for embryos developing from the 2-cell stage on Day 1 which represented the majority (69.7%) of embryos. Evenness of division was featured in the interaction terms associated with 2- and 4-cell embryos on Day 2 and, accordingly, reduced probability values were estimated in such embryos

exhibiting asymmetry of division (see also Fig. 5 and Table 3). The negative relationship between cleavage time and probability of blastocyst development (see Tables 1 and 3) was reproduced in the full model and is illustrated in Table 6 as the reduced estimated probabilities of embryos that cleaved at 27 h compared to those that divided at 21 h post- insemination. The use of amino acid score as another contributory variable to predict blastocyst development (Table 3) is also faithfully incorporated into the full model whereby lower amino acid scores derived from the discriminant analysis generate higher estimated probability values. TABLE 1:

Table 1 shows the relationship between time of first observed cleavage post-insemination and subsequent blastocyst rate. This relationship was significant on analysis of all cleaving embryos (PO.001) and, after segregation, in those in which the cleavage was regarded as cyto-numerically normal (2-cell embryos) (P<0.001) or cyto-numerically precocious (>3-cell embryos) (P=0.011) for this stage of development.

Time of AU cleaving 2-cell embryos >3 -cell embryos cleavage post embryos only insemination Blastocysts Blastocysts Blastocysts n n n (h) (%) (%) (%)

21 43 53.5 38 58.0 5 60.0

23 92 32.6 71 31.2 21 42.9

25 102 24.5 68 28.8 34 29.4

27 56 14.3 34 12.4 22 18.2

29 43 18.6 22 38.7 21 14.3

31 20 4.8 15 0 5 20.0

TABLE 2:

Table 2 shows the net rates of amino acid depletion (negative values) and appearance (positive values) and total net rates of amino acid and nitrogen appearance, depletion, balance and turnover in fast and slow cleaving embryos. Fast and slow cleaving embryos were defined as those cleaving between 21-25 and 27-31 h post insemination, respectively.

Rates (pmol/embryo/h)*

Parameter Fast cleaving Slow cleaving P-value embryos (n=211) embryos (n= 114)

Glycine 0.356 ±0.020 0.328 ± 0.022 NS

Alanine 0.094 ±0.014 0.082 ±0.015 NS

Leucine 0.101 ±0.004 0.101 ±0.005 NS

Isoleucine 0.053 ± 0.003 0.053 ± 0.002 NS

Valine 0.048 ± 0.002 0.043 ± 0.002 NS

Phenylalanine 0.037 ± 0.003 0.047 ± 0.005 NS

Tryptophan 0.009 ±0.005 0.024 ± 0.008 NS

Tyrosine 0.031 ±0.003 0.031 ±0.004 NS

Methionine 0.011 ±0.004 0.029 ± 0.005 O.001

Serine 0.084 ±0.013 0.081 ±0.015 NS

Threonine -0.777 ±0.042 -0.742 ±0.049 NS

Asparagine 0.509 ±0.011 0.455 ±0.013 0.004

Glutamine -1.405 ±0.033 -1.372 ±0.042 NS

Lysine 0.104 ±0.023 0.159 ±0.021 NS

Arginine -0.165 ±0.023 -0.076 ±0.010 0.04

Histidine 0.026 ±0.005 0.032 ±0.004 NS

Glutamic acid 0.242 ±0.009 0.245 ±0.011 NS

Aspartic acid 0.106 ±0.007 0.094 ±0.008 NS

Amino acid appearance 2.021 ± 0.075 1.939 ±0.095 NS

Amino acid depletion -2.559 ±0.095 -2.326 ±0.115 0.013

Amino acid balance -0.537 ±0.064 -0.386 ±0.072 NS

Amino acid turnover 4.580 ±0.158 4.265 ±0.198 0.027

Nitrogen appearance 2.831 ±0.103 2.705 ±0.130 NS

Nitrogen depletion -4.597 ±0.182 -3.991 ±0.197 0.001

Nitrogen balance -1.765 ±0.128 -1.256 ±0.122 0.024

Nitrogen turnover 7.428 ± 0.267 6.695 ±0.311 0.005

* All rates differed significantly from zero (P<0.001).

TABLE 3: Table 3 shows univariate analyses of individual predictors by logistic regression detailing coefficients estimates, levels of significance and odds ratios±95% confidence intervals (CI).

WaId Odds

Potential predictor variables B α S.E. # P-value $ statistic 95% CI for odds ratio ratio

Cleavage time -0.240 0.051 21.852 O.001 0.787 0.711 0.870

Dayl@2-cell* -0.080 0.259 0.95 0.758 0.923 0.556 1.534

Dayl@3-cell* -0.001 0.361 0 0.998 0.999 0.493 2.025

Dayl@4-cell* 0.703 0.382 3.385 0.066 2.019 0.955 4.269

Day 1: Evenness of division -0.291 0.204 2.039 0.153 0.748 0.502 1.114

Day 1: Degree of fragmentation -0.592 0.228 6.766 0.009 0.553 0.354 0.864

Day2@2-cell* -2.021 0.442 20.938 O.001 0.133 0.056 0.315

Day2@3-cell* -0.778 0.330 5.549 0.018 0.459 0.240 0.877

Day2@4-cell* 1.549 0.255 36.980 O.001 4.707 2.857 7.755

Day 2: Evenness of division -0.416 0.190 4.810 0.028 0.659 0.455 0.957

Day 2: Degree of fragmentation -0.642 0.203 10.002 0.002 0.526 0.353 0.783

Amino acid score -0.643 0.138 21.672 <0.001 0.526 0.401 0.689

* Categorical values of blastomere number were dummy coded for the logistic regression. The coding scheme for Day 1 embryos was as follows: Dayl@2cell (1 if 2-cell, 0 otherwise), Dayl@3-cell (1 if 3-cell, 0 otherwise) and Dayl@4-cell (1 if 4-cell, 0 otherwise). According to this categorization method, 5-8 cell embryos would be coded 0. Blastomere numbers of embryos on Day 2 were coded similarly. α Coefficient estimate of logistic regression.

* Standard error of B.

$ P-value of WaId statistic.

'ABLE 4: Table 4 shows classification matrices for selected logistic regression models illustrating the predictive accuracy of variables xamined either individually or multivariately. The table also presents the goodness of fit statistic, pseudo R 2 , for each model.

Predicted outcome

Fate Percentage correct

Observed Pseudo edictor variables entered in model outcome Blastocysts

Per fate _ , it Added correctly R 2

Degenerate Blastocyst class Overall$ value* classified*

Degenerate 227 9 96.2 nino acid score 72.1 -3.4 40.0 0.066

Blastocyst 81 6 6.9

Degenerate 261 0 100 iy 1: Number of blastomeres 74.4 0 0

90 0 0 0.047

Blastocyst iy 1: Number of blastomeres, evenness of division and degree Degenerate 261 0 100 74.4 0 0 0.025 fragmentation Blastocyst 90 0 0

Degenerate 255 6 97.7 iy 1: Number of blastomeres and cleavage time 73.4 -1.1 45.5 5 5.4 0.067

Blastocyst 88 iy 1: Number of blastomeres, evenness of division, degree of Degenerate 255 5 98.1 74.4 0 50.0 0.080 & igmentation and cleavage time Blastocyst 85 5 5.6

Degenerate 261 0 100 iy 2: Number of blastomeres 74.6 0 0 0 0 0.113

Blastocyst 89 iy 2: Number of blastomeres, evenness of division and degree Degenerate 227 34 87 77.4 11.2 56.4 0.152 fragmentation Blastocyst 45 44 49.4

Degenerate 211 50 80.8 iy 1 and Day 2: Number of blastomeres 75.7 4.5 51.9 0.130

Blastocyst 35 54 60.7

Degenerate 238 23 91.2 iy 1 and Day 2: Number of blastomeres and cleavage time 80.1 19.8 63.5 0.223

Blastocyst 46 40 46.5 iy 1 and Day 2: Number of blastomeres, evenness of division, Degenerate 235 25 90.4 81.6 27.3 66.2 0.232 gree of fragmentation and cleavage time Blastocyst 39 49 55.7 iy 1 and Day 2: Number of blastomeres, evenness of division, Degenerate 224 10 95.7 84.2 39.0 80.8 0.266 gree of fragmentation, cleavage time and amino acid score Blastocyst 40 42 51.2

$ The percentage of embryos correctly classified as blastocysts and degenerate (the hit ratio).

* The added value is the percentage of correct classifications above the number that can be correctly predicted by simply choosing the largest category (i.e. degenerate embryos) for all cases.

* The percentage of blastocysts correctly classified as a proportion of those embryos predicted to become blastocysts.

TABLE 5: Table 5 shows the fitted logistic regression model as a predictor of blastocyst formation in early in vitro produced pig embryos. Variables separated by asterisks represent interaction terms.

WaId P- Odds 95% C.I. δ for

Predictor variables B α SJE.* statistic value $ ratio odds ratio

Cleavage time -0.159 0.061 6.800 0.009 0.853 0.758 0.961

Amino acid score -0.727 0.162 20.135 <0.001 0.483 0.352 0.664

CDayl@2-cell)*(Day2@4-cell) 1.712 0.517 10.970 0.001 5.539 2.011 15.255

(T)ayl@2-ceU)*(Evenness of division on Day l)*(Day2@3-cell) -0.365 0.176 4.295 0.038 0.694 0.491 0.980

(X>ayl@4-cell)*(Day2@4-cell) 1.667 0.804 4.296 0.038 5.296 1.095 25.613

(Day2@2-cell)*(Evenness of division on Day 2) -0.694 0.221 9.864 0.002 0.500 0.324 0.770

(Day2@4-cell)* (Evenness of division on Day 2)*(Degree of fragmentation on Day 2) -0.204 0.114 3.218 0.073 0.815 0.652 1.019

4- 4- Intercept 0.501 0.666 _

α Coefficient estimate of logistic regression.

# Standard error of B.

$ P-value of WaId statistic. δ Confidence intervals.

TABLE 6: Table 6 shows estimated probabilities of porcine blastocyst formation according to cell number on Days 1 and 2, evenness of division on Day 2, cleavage time post-insemination and amino acid scores and derived from the fitted logistic regression model.

Only a selection of variable permutations are illustrated. Values for evenness of cell division and degree of fragmentation on Day 1 were classified as 2 and 0, respectively. Degree of fragmentation on Day 2 was classified as 0. Slow and fast cleaving embryos are illustrated by the selection of those embryos cleaving at 21 and 27 h post-insemination, respectively. The amino acid scores are derived from the discriminant function analysis; values of the first and third quartile of the score distribution are illustrated here as Low and High scores i.e embryos exhibiting low amino acid scores have a greater probability of developing to blastocysts. Estimated probability values >0.5 (underlined) represent combinations of variables that are likely to be conducive to blastocyst development.

Day l Day 2

Amino acid

Low High score

Cleavage

21 .7 21 27 time (h)*

Evenness

2 4 2 4 2 4 2 4 of division*

Cell Cell number on number on Probability values Day l Day 2

2 2 0.21 0.06 0.09 0.02 0.08 0.02 0.03 0.01 3 0.33 0.33 0.16 0.16 0.15 0.15 0.06 0.06 4 0.79 0.72 0.59 0.50 0.57 0.47 0.34 0.25

5-8 0.51 0.51 0.29 0.29 0.26 0.26 0.12 0.12

3 3 0.51 0.51 0.29 0.29 0.26 0.26 0.12 0.12 4 0.41 0.31 0.21 0.15 0.19 0.14 0.08 0.06 5-8 O 1 M O51 0.29 0.29 0.26 0.26 0.12 0.12 4 4 0.79 0.71 0.58 0.48 0.56 0.45 0.33 0.24

5-8 0.51 0.51 0.29 0.29 0.26 0.26 0.12 0.12

* Hours post-insemination.

$ Only the two extremes of evenness of division are illustrated here, namely the scoring categories of 2 and 4 (see Fig. 1.).

DISCUSSION

The method of the present invention combines prognostic factors by multivariate computation. This is a far more powerful technique for predictive purposes than could be achieved univariately. In this regard using our own data, cell number, evenness of division and degree of fragmentation on Day 2, together with cleavage time were univariately related to blastocyst formation, yet no factor, in isolation, could be used to predict whether an individual embryo was destined to become a blastocyst. In contrast, a logistical regression model comprising simply blastomere numbers, evenness of division and degree of fragmentation on Day 2 correctly classified 49% of the available blastocysts; equivalent to

56% of the blastocysts in the predicted population. The ability to predict blastocyst formation was also considerably different when using the morphological data gathered from either Day

1 or Day 2 since, in contrast to the Day 2 data, only degree of fragmentation had been shown to be related to blastocyst formation on Day 1 by univariate analysis. Even appending the kinetic data in the model to the morphological features from Day 1 did not raise the proportion of predicted blastocysts of those observed to beyond 6%. The unusual cytokinetics of the first cleavage division and the weak effect of asymmetry of cleavage on blastocyst formation (vide infra) were the undoubted explanations for this dichotomy.

Surprisingly, a relatively effective model for the prediction of blastocyst formation is that based on the interaction of dummy variates coding for blastomere numbers on Days 1 and 2; namely, interactions between 2-cell embryos on Day 1 with 4-cell embryos on Day 2, and between 4-cell embryos on Days 1 and 2. Such a system identified over 60% of the observed blastocysts generating an approximate 50% split between degenerate embryos and blastocysts in the predicted group. The importance of time of cleavage as a predictor or

porcine blastocyst formation was highlighted by the beneficial effect of adding this factor into a model containing purely blastomere numbers on Days 1 and 2, by which 11.5% more predicted embryos constituted blastocysts although the proportion of blastocysts correctly identified was reduced. The addition of symmetry of division and degree of fragmentation recorded on Days 1 and 2 into this model again improved the predictive power of the analysis emphasising the value of these morphological features when combined interactively with other prognostic variates. The final factor to be amalgamated into the model was amino acid score which was of particular interest owing to the correlation between this variate and the implantation rate of human embryos [24]. Our results establish that, univariately, amino acid score is significantly related to blastocyst formation and can improve the accuracy of blastocyst prediction by surprisingly substantial levels when assimilated into a model containing other relevant variables. Incorporation of amino acid score into the analysis to generate the final model improved the proportion of accurately predicted blastocysts to over 80% representing an improvement of over 14% from the previous model.

Asymmetry of division and degree of fragmentation are likely products of insufficient in vivo maturation and/or effects of inadequate culture conditions compromising cytoskeletal patency [53, 57]. In addition to these problems, pig in vitro production systems suffer from polyspermia [55] which further alters the normal pattern of cytokinetic events, and can affect viability in an unpredictable manner [64]. Any embryos in our studies that divided to either >2-cells during their initial cleavage or >/=5-cells 24 h later were categorized as either fragmenting or cytokinetically abnormal. Indeed, Wang et al. [57] found that by 24 h post- insemination, 72, 5, 17 and 7% of cleaved IVP pig embryos were at the 2, 3, 4 and 5-8 cell

stage (largely in agreement with the data presented here) and that 27, 50, 86 and 100% of these embryos contained blastomeres that were anucleate and/or binucleated. In the present work, such abnormal embryos that contained >2 cells at first cleavage were remarkable, in that, although representing only 30.3% of cleaved embryos on Day 1, the 3-cell embryos on Day 1 produced a blastocyst production of 27% which was equivalent to that produced by 2- cell embryos (which are regarded as cytokinetically normal), while embryos that cleaved initially to 4-cells on Day 1 achieved a 40% blastocyst yield. With regard to the mechanisms responsible for abnormal cleavage patterns, factors such as the number of supernumerary sperm-derived mitotic spindles, their proximity to one-another, and asynchrony in male pronuclear formation (all of which are commonly observed in IW pig embryos), are possible causes [30, 65]. Other peculiarities in cytokinetics observed in the present study were the apparent loss of blastomeres in some embryos after 24 h; a phenomenon most likely caused either by the subsequent failure of cytokinesis between blastomeres that appeared to be cleaved at the time of observation, or by blastomere fusion [78, 79].

The pattern of amino acid appearance and depletion rates have been shown to differ in arresting and developing human embryos in vitro [23] and have been used as a predictor of implantation potential [24]. Together with our previous studies in IVP pig embryos [28], the results of Houghton et al. [23] and Brison et al. [24] all indicate that there are developmental changes in the patterns of depletion and appearance of individual amino acids by preimplantation embryos. In addition, amino acids that exhibit significantly different patterns of depletion or release between arresting and developing embryos may differ according to the stage of embryo examined. Of the predictive amino acids observed in our current study,

glycine corresponded to those observed by Houghton et al. [23] and Brison et al. [24]. However, the only amino acids (methionine, asparagine and arginine) in the present study that were differentially released or depleted between slow and fast cleaving embryos were identical to three out of five amino acids whose depletion/appearance differed between arresting and developing human embryos on Day 2-3 [23]. How delayed cleavage and the associated inferior morphological quality could modify metabolism or, more specifically, patterns of amino acid uptake and release remains to be resolved but might be connected to oocyte cytoplasmic quality (as described above). One such example is the expression of glucose-6-phosphate dehydrogenase, a constituent enzyme of the pentose phosphate pathway that also functions as a marker of cytoplasmic immaturity in pig oocytes [60, 61]. Another example is the different rates of glucose and pyruvate uptake between adult and pre-pubertal 2-4 cell bovine embryos [80], again suggestive of differential oocytic competence [62]. However, if polyspermia is involved, our previous research has already established that multiple sperm penetration can alter the rates of amino acid appearance and consumption [28].

Domestic animals, specifically those of pigs and cattle, present special challenges for noninvasive morphological investigation owing to the large amount of cytoplasmic lipid [39] that effectively precludes the observation of nuclei and hinders or prevents the characterization of cytoplasmic structure, rendering apparently useful markers of viability in human embryos [40] inapplicable to the pig and cow [41]. Cytokinetϊc abnormalities are also common in pig embryonic development.

The results of the porcine model demonstrate the principle of using amino acid profiling to provide additional predictive power in the selection of viable embryos. The porcine model is widely accepted in the field as one of the most relevant animal models for the human that is currently available.

The invention provides a method to more reliably and non-invasively predict which early embryos have the ability to develop to blastocyst stage and/or beyond (i.e, the ability to predict pregnancy). It is accepted that predictive power of Amino Acid Profiling (AAP) will vary between different species - with factors like different rates of aneuploidy having a role, but the principle of AAP will still apply. The more the variability that exists between individual embryos, the greater the power of AAP. This is why AAP does not seem to work well for embryos from inbred mice of the same strain. Since humans comprise a random mating population, the predictive power of the model in humans will be particularly enhanced.

In analysing the amino acid data, the discriminant analysis method of the invention reduces (or amalgamates) 18 amino acid values to just one value for each embryo. 'Amino Acid Score' as used herein refers to the amalgamated score. In considering the predictive value of the amino acid data, the data indicates that the logistic regression of Amino Acid Score alone is highly significant and can correctly classify 40% of blastocysts in those embryos picked (Table 3). However only 6 blastocysts out of a total of 87 have been identified (i.e. only 6.9%). The penultimate row of Table 4 (i.e., results without the amino acid data) shows 66.2% of blastocysts were correctly identified in the pick, representing 55.7 % of the total

number of blastocysts available. Adding the Amino Acid Score to this model (bottom row, Table 4) substantially raises the number of correctly identified blastocysts in the pick by 14.6% to 80.8. The four values in the Classification Matrix (see Table 4), representing the Predicted and Observed outcomes therefore provide a simple summary of the effectiveness of the model.

Table 4 (in which amino acid scores are combined with all the other variates measured) shows that Amino Acid Score (in our Table 5) remains highly significant in the full model (P<0.001). Amino Acid Score is therefore truly independent of other variates (e.g., morphological and kinetic markers) and cannot be replaced by them. Amino Acid Score therefore augments the predictive value of the model.

REFERENCES

1. Doyle P 1996 The outcome of multiple pregnancy Human Reproduction 11 Suppl 4: 110-7; discussion 118-120

2. Kashiwazaki N, Kikuchi K, Hirabayashi M, Shimada A, Noguchi J, Takahashi R, Shino M, Kaneko H & Ueda M 1998 Viability after transfer to recipients of porcine embryos produced in vitro Theriogenology 49244

3. Booth PJ 2002 Potential disease risks associated with advanced embryo technologies in mammals induced by modificiation of the embryonic environment, embryo manipulation and retroviral activation. The 2 nd International Symposium on Assisted

Reproductive Technology (ART) for the Conservation and Genetic Management of Wildlife Henry Doorly Zoo, Omaha, Nebraska, 28-29 Sept 2002, pl51-158.

4. Edwards RG, Fishel SB, Cohen J, Fehilly CB, Purdy JM, Slater JM, Steptoe PC & Webster JM 1984 Factors influencing the success of in vitro fertilization for alleviating human fertility Journal of In Vitro Fertilization and Embryo Transfer 1 3- 23

5. Lonergan P, Fair T & Gordon I 1992 Effect of time of transfer to granulosa cell monolayer and cell stage at 48 hours post-insemination on bovine oocyte development following IVM/TVF/rVC 8" 1 Meeting of the European Embryo Transfer Association Lyon 11-12 September 136

6. Van Soom A, Van Vlaenderen I, Mahmoudzadeh AR & de Kruif A 1992 Compaction rate of in vitro fertilized bovine embryos related to the interval from insemination to first cleavage Theriogenology 38 905-919

7. Kobayashi T, Kato Y & Tsunoda Y 2004 Effect of the timing of the first cleavage on the developmental potential of nuclear-transferred mouse oocytes receiving embryonic stem cells Theriogenology 62 854-860

8. Gonzales DS, Pinheiro JC & Bavister BD 1995 Prediction of the developmental potential of hamster embryos in vitro by precise timing of the third cell cycle Journal of Reproduction and Fertility 105 1-8

9. Bavister BD, Boatman DE, Leibfried L, Loose M & Vernon MW 1983 Fertilization and cleavage of rhesus monkey oocytes in vitro Biology of Reproduction 28 983-999.

10. Ziebe S, Petersen K, Lindenberg S, Andersen A-G, Gabrielsen A & Nyboe Andersen A 1997 Embryo morphology or cleavage stage: how to select the best embryos for transfer after in vitro fertilization Human Reproduction 12 1545-1549

11. Racowsky C, Combelles CMH, Nureddin A, Pan Y, Finn A, Miles L, Gale S O'Leary T & Jackson KV 2003 Day 3 and day 5 morphological predictors of embryo viability Reproductive BioMedicine Online 6 323-331

12. Puissant F, Van Rysselberge M, Barlow P, Deweze J & Leroy F 1987 Embryo scoring as a prognostic tool in IVF treatment Human Reproduction 2 705-708

13. Steer CV, Mills CL, Tan SL, Campbell S & Edwards RG 1992 The cumulative embryo score: a predictive embryo scoring technique to select the optimal number of embryos to transfer in an in-vitro fertilization and embryo transfer programme Human Reproduction 7 117-119

14. Fisch JD, Rodriguez H, Ross R, Overby G & Sher G 2001 The Graduated Embryo Score (GES) predicts blastocyst formation and pregnancy rate from cleavage-stage embryos Human Reproduction 16 1970-1975

15. De Placido G, Wilding M, Strina I, Alviggi E, Alviggi C, Mollo A, Varicchio MT, Tolino A, Schiattarella C & Dale B 2002 High outcome predictability after IVF using a combined score for zygote and embryo morphology and growth rate Human Reproduction 172402-2409

16. Scott LA & Smith S 1998 The successful use of pronuclear embryo transfers the day following oocyte retrieval Human Reproduction 13 1003-1013.

17. Tesarik J & Greco E 1999 The probability of abnormal preimplantation development can be predicted by a single static observation on pronuclear stage morphology Human Reproduction 14 1318-1323

18. Ebner T, Moser M, Yaman C, Feichtinger O, Haiti J & Tews G 1999 Elective transfer of embryos selected on the basis of first polar body morphology is associated with increased rates of implantation and pregnancy Fertility and Sterility 72599-603

19. Garello C, Baker H, Rai J, Montgomery S, Wilson P, Kennedy CR & Hartshorne GM 1999 Pronuclear orientation, polar body placement, and embryo quality after intracytoplasmic sperm injection and in-vitro fertilization: further evidence for polarity in human oocytes? Human Reproduction 142588-2595

20. Moon J-H, Hyun C-S, Lee S-W, Son W-Y 5 Yoon S-H & Lim J-H 2003 Visualisation of the metaphase II meiotic spindle in living human oocytes using the Polscope enables the prediction of embryonic developmental competence after ICSI Human Reproduction 18 817-820

21. Donnay I 2002 Metabolic markers of embryo viability In Assessment of Mammalian Embryo Quality: Invasive and Non-invasive Techniques, pp57-94. Eds A Van Soom & M Boerjan. Dordrecht, Netherlands: Kluwer Academic.

22. Yie S-M, Balakier H, Motamedi G & Librach CL 2005 Secretion of human leukocyte antigen-G by human embryos is associated with a higher in vitro fertilization pregnancy rate Fertility and Sterility 83 30-36

23. Houghton FD, Hawkhead JA, Humpherson PG, Hogg JE, Balen AH, Rutherford AJ & Leese HJ 2002 Non-invasive amino acid turnover predicts human embryo developmental capacity. Human Reproduction 17 999-1005.

24. Brison DR, Houghton FD, Falconer D, Roberts SA, Hawkhead J, Humpherson PG, Lieberman BA & Leese HJ 2004 Identification of viable embryos in IVF by noninvasive measurement of amino acid turnover. Human Reproduction 19 2319-2324.

25. Stokes PJ, Abeydeera LR & Leese HJ 2005 Development of porcine embryos in vivo and in vitro; evidence for embryo 'cross talk' in vitro. Developmental Biology 284 62-71

26. Abeydeera LR & Day BN 1997 Fertilization and subsequent development in vitro of pig oocytes inseminated in a modified tris-buffered medium with frozen-thawed ejaculated spermatozoa. Biology of Reproduction 57 729-734.

27. Petters RM & Reed ML 1991 Addition of taurine and hypotaurine to culture medium improves development of one- and two-cell pig embryos in vitro. Theriogenology 35:253.

28. Booth PJ, Humpherson PG, Watson TJ and Leese HJ 2005 Amino acid depletion and appearance during porcine preimplantation embryo development in vitro Reproduction 130 655-668

29. Tay JI, Rutherford AJ, Killick SR, Maguiness SD, Partridge RJ & Leese HJ. 1997 Human tubal fluid: production, nutrient composition and response to adrenergic agents. Human Reproduction 122451-2456.

30. Han Y-M, Wang W-H, Abeydeera LR, Petersen AL, Kim J-H, Murphy C, Day BN & Prather RS 1999b Pronuclear location before the first cell division determines ploidy of polyspermic pig embryos Biology of Reproduction 61 1340-1346.

31. Mateusen B, Van Soom A, Maes DGD, Donnay I, Duchateau L & Lequarre A-S 2005 Porcine embryo development and fragmentation and their relation to apoptotic

markers: a cinematographic and confocal laser scanning microscopic study Reproduction 129443-452

32. Lamb VK & Leese HJ. 1994 Uptake of a mixture of amino acids by mouse blastocysts. Journal of Reproduction and Fertility 102 169-175.

33. Pemble LB & Kaye PL 1986 Whole protein uptake and metabolism by mouse embryos. Journal of Reproduction and Fertility IS 149-157.

34. Orsi NM & Leese HJ 2004 Amino acid metabolism of preimplantation bovine embryos cultured with bovine serum albumen or polyvinyl alcohol. Theriogenology 61 561-572.

35. Hair JF, Anderson RE, Tatham RL & Black WC (Eds) 1995 In Multivariate Data Analysis, edn 4., London: Prentice Hall.

36. Menard S 2002 In Applied Logistic Regression Analysis, edn 2. Thousand Oaks: Sage Publications.

37. Jaccard J 2001 In Interaction Effects in Regression Analysis. Thousand Oaks: Sage Publications.

38. Bendel RB & Afifl AA 1977 Comparison of stopping rules in forward "stepwise" regression. Journal of the American Statistical Association 72 46-53.

39. Sturmey RG & Leese HJ 2003 Energy metabolism in pig oocytes and early embryos. Reproduction 126 197-204.

40. Alikani M, Sadowy S & Cohen J 2002 Human embryo morphology and developmental capacity In Assessment of Mammalian Embryo Quality: Invasive and Non-invasive Techniques, ppl-31. Eds: A Van Soom & M Boerjan. Kluwer Academic Publishers

41. Van Soom A, Mateusen B, Leroy J & de Kruif 2003 Assessment of mammalian embryo quality: what can we learn from embryo morphology? Reproductive BioMedicine Online 7 664-670

42. Edwards RG 2002 Aspects of the molecular regulation of early mammalian development Reproductive BioMedicine Online 6 97-113

43. Yadav BR, King WA & Betteridge KJ (1993) Relationships between the completion of first cleavage and the chromosomal complement, sex, and developmental rates of bovine embryos generated in vitro Molecular Reproduction and Development 36434- 439

44. Lonergan P, Khatir H, Piumi F, Rieger D, Humblot P & Boland MP (1999) Effect of time interval from insemination to first cleavage on the developmental characteristics, sex ratio and pregnancy rate after transfer of bovine embryos Journal of Reproduction and Fertility 117 159-167

45. Fenwick J, Platteau P, Murdoch AP & Herbert M 2002 Time from insemination to first cleavage predicts developmental competence of human preimplantation embryos in vitro Human Reproduction 17 407-412

46. Van Soom A, Ysebaert M-T & De Kruif A 1997 Relationship between timing of development, morula morphology, and cell allocation to inner cell mass and trophectoderm in in vitro-produced bovine embryos Molecular Reproduction and Development 47 47-56

47. Lundin K, Bergh C & Hardarson T 2001 Early embryo cleavage is a strong indicator of embryo quality in human IVF Human Reproduction 16 2652-2657

48. Salumets A, Hyden-Granskog C, Makinen S, Suikkari A-M, Tiitinen A & Tuuri T 2003 Early cleavage predicts the viability of human embryos in elective single embryo transfer procedures Human Reproduction 18 821-825

49. Van Montfoort APA, Dumoulin JCM, Kester ADM & Evers JLH 2004 Early cleavage is a valuable addition to existing embryo selection parameters: a study using single embryo transfers Human Reproduction 192103-2108

50. Grupen CG, Nagashima H & Nottle MB 1997 Asynchronous meiotic progression in porcine oocytes matured in vitro: a cause of polyspermic fertilization? Reproduction, Fertility and (Development 9 187-191

51. Dominko T & First NL 2003 Timing of meiotic progression in bovine oocytes and its effect on early embryo development Molecular Reproduction and Development 47 456-467

52. Hardarson T, Hanson C, Sjogren A & Lundin K 2001 Human embryos with unevenly sized blastomeres have lower pregnancy and implantation rates: indications for aneuploidy and multinucleation. Human Reproduction 16313-318

53. Albertini DF, Sanfins A & Combelles CMH 2003 Origins and manifestations of oocyte maturation competencies Reproductive BioMedicine Online 6410-415

54. Boiso I, Veiga A & Edwards RG 2002 Fundamentals of human embryonic growth in vitro and the selection of high-quality embryos for transfer. Reproductive BioMedicine Online 5 328-350.

55. Funahashi H 2003 Polyspermic penetration in porcine IVM-IVF systems Reproduction, Fertility and Development 15 167-177

56. Kim N-H, Funahashi H, Prather RS, Schatten G & Day BN 1996 Microtubule and microfilament dynamics in porcine oocytes during meiotic maturation Molecular Reproduction and Development 43 248-255

57. Wang W-H, Abeydeera LR, Han Y-M, Prather RS & Day BN (1999) Morphologic evaluation and actin filament distribution in porcine embryos produced in vitro and in vivo Biology of Reproduction 60 1020-1028

58. Wang W-H, Abeydeera LR, Prather RS & Day BN (1998) Morphologic comparison of ovulated and in vitro-matured porcine oocytes, with particular reference to polyspermy after in vitro fertilization Molecular Reproduction and Development 49 308-316

59. Nagashima H, Grupen CG, Ashman RJ and Nottle MB 1996 Developmental competence of in vivo and in vitro matured porcine oocytes after subzonal injection Molecular Reproduction and Development 45 359-363

60. Ericsson SA, Boice ML, Funahashi H & Day BN 1993 Assessment of porcine oocytes using brilliant cresyl blue Theriogenology 39 p214

61. Roca J, Martinez E, Vazquez JM & Lucas X 1998 Selection of immature pig oocytes for homologous in vitro penetration assays with the brilliant cresyl blue test Reproduction Fertility and Development 10479-485

62. Gandolfi F, Vassena R and Lauria A 2000 The developmental competence of the oocyte before puberty: is something missing? Reproduction in Domestic Animals 35 66-71

63. JJkeda K & Takahashi Y 2003 Comparison of maturational and developmental parameters of oocytes recovered from prepubertal and adult pigs Reproduction, Fertility and Development 15 215-221

64. Han Y-M, Abeydeera LR, Kim J-H, Moon H-B, Cabot RA, Day BN & Prather RS 1999a Growth retardation of inner cell mass cells in polyspermic porcine embryos produced in vitro Biology of Reproduction 60 1110-1113.

65. Munne S & Cohen J 1998 Chromosome abnormalities in human embryos Human Reproduction Update 4 842-855

66. Shire JGM & Whitten WK 1980 Genetic variation in the timing of first cleavage in mice: effect of maternal genotype Biology of Reproduction 23 369-376

67. Warner CM, Cao W, Exley GE, McElhinny AS, Alikani M, Cohen J, Scott RT & Brenner CA 1998 Genetic regulation of egg and embryo survival Human Reproduction 13 Suppl 3 178-196

68. Han Z, Chung YG, Goa S & Latham KE 2005 Maternal factors controlling blastomere fragmentation in early mouse embryos Biology of Reproduction 72 612- 618

69. Hao Y, Lai L, Mao J, Im G-S, Bonk A & Prather RS 2003 Apoptosis and in vitro development of preimplantation porcine embryos derived in vitro or by nuclear transfer Biology of Reproduction 69 501-507

70. Antczak M & Van Blerkom J 1999 Temporal and spacial aspects of fragmentation in early human embryos: possible effects on developmental competence and association with the differential elimination of regulatory proteins from polarized domains Human Reproduction 14429-447

71. Ebner T, Yaman C, Moser M, Sommergruber M, PoIz W & Tews G 2001 Embryo fragmentation in vitro and its impact on treatment and pregnancy Fertility and Sterility 76281-285

72. Hnida C, Engenheiro E & Ziebe S 2004 Computer-controlled, multilevel, morphometric analysis of blastomere size as biomarker of fragmentation and multinuclearity in human embryos Human Reproduction 19 288-293

73. Rath D, Freitag K, Niemann H, Sieg B. Continuous control of porcine embryo development in vitro. Theriogenology 1998; 49:215.

74. Kola I, Trounson A, Dawson G & Rogers P 1987 Tripronuclear human oocytes: altered cleavage patterns and subsequent karyotypic analysis of embryos Biology of Reproduction 37 395-401

75. McCauley TC, Mazza MR, Didion BA, Mao J, Wu G, Coppola G, Coppola GF, Di Berardino D & Day BN 2003 Chromosomal abnormalities in Day-6 in vitro-produced pig embryos Theriogenology 60 1569-1580

76. Everett CA & West JD 1996 The influence of ploidy on the distribution of cells in chimaeric mouse blastocysts Zygote 4 59-66

77. Picton H, Houghton F, Harris S, Clyde J, Hawkhead J, Rutherford A, Hogg J & Leese H 2004 Aneuploidy and ammo acid turnover in early human embryos Human Reproduction 19 Suppl 1 O-062

78. Balakier H, Cabaca O, Bouman D, Shewchuk AB, Laskin C & Squire JA 2000 Spontaneous blastomere fusion after freezing and thawing of early human embryos leads to polyploidy and chromosomal mosaicism Human Reproduction 15 2404-2410

79. Hardarson T, Lofinan C, Coull G, Sjogren A, Hamberger L & Edwards RG 2002 Intemalisation of cellular fragments in a human embryo: time-lapse recordings. Reproductive Biomedicine Online 5 36-38

80. Steeves TE, Gardner DK, Zuelke KA, Squires TS & Fry RC 1999 In vitro development and nutrient uptake by embryos derived from oocytes of pre-pubertal and adult cows Molecular Reproduction and Development 5449-56

81. Giorgetti C, Terriou P, Auquier P, Hans E, Spach J-L, Salzmann J and Roulier R 1995 Embryo score to predict implantation after in- vitro fertilization: based on 957 single embryo transfers Human Reproduction 10 2427-2431

82. Rijnders PM and Jansen CAM 1998 The predictive value of day 3 embryo morphology regarding blastocyst formation, pregnancy and implantation rate after day 5 transfer following in-vitro fertilization or intracytoplasmic sperm injection Human Reproduction 13 2869-2873

83. Milki AA, Hinckley MD, Gebhardt J, Dasig D, Westphal LM and Behr B 2002 Accuracy of day 3 criteria for selecting the best embryos Fertility and Sterility 77 1191-1195

84. Scott LA & Smith S 1998 The successful use of pronuclear embryo transfers the day following oocyte retrieval Human Reproduction 13 1003-1013

85. Van Royen E, Mangelschots K, De Neubourg D, Valkenburg M, Van de Meerssche M, Ryckaert G, Eestermans W and Gerris J 1999 Characterisation of a top quality embryo, a step towards single-embryo transfer Human Reproduction 142345-2349

86. Vajta G, Peura TT, Holm P, Paldi A, Greve T, Trounson AO & Callesen H 2000 New method for culture of zona-included or zona-free embryos: the well of the well (WOW) system Molecular Reproduction and Development 55 256-264

87. Diaz-Cuero L & Gerton GL 2001 The influence of growth factors on the development of preimplantation mammalian embryos Archives in Medical Research 32 619-626

88. Edwards RG & Beard HK Is the success of human IVF a matter of developmental biology? In Towards Reproductive Certainty Eds R Jansen & D Mortimer Parthenon Publishing Group, New York 1999414-420

89. Hardy K, Spanos S, Becker D, Iannelli P, Winston RML & Stark J 2001 From cell death to embryo arrest: Mathematical models of human preimplantation embryo development PNAS 98 1655-1660

90. Oatway C, Gunby J & Daya S 2004 Day three versus day two embryo transfer following in vitro fertilization or intracytoplasmic sperm injection Cochrane Database Systematic Review CD004378

91. Blake D, Proctor M, Johnson N & Olive D 2002 Cleavage stage versus blastocyst stage embryo transfer in assisted conception Cochrane Database Systematic Review CD002118

92. Gerris J, Van Royen E, De Neubourg D, Mangelschots K, Valkenburg M, Ryckaert G. Impact of single embryo transfer on the overall and twin pregnancy rates of an rVF/ICSI programme. RBM Online 2001; 2:172-177.