FIELD OF THE INVENTION

5 The present invention relates to a manufacture and use of gardening and landscaping materials that provide an immunomodulatory effect. The novel materials are advantageous in providing materials for landscaping and gardening that are able to modulate the immune response of a subject being in contact with the materials.

BACKGROUND OF THE INVENTION

10 Recent findings have shown that certain natural organic soil hosts a rich microbial community consisting mostly of non-culturable and slow-growing bacteria. These slow-growing and often dormant bacteria prevail in certain types of soil materials, as they tend to outcompete fast-growing soil bacteria in a heterogenic environment where limiting resources are scarce and sporadic (Kaiser et al. 2015, Coyte et al.

15 2016). Interestingly, a large proportion of bacteria on human skin is also dormant or slow-growing (Alexeyev 2013, Jones and Lennon 201 1 ). The reason may be that on skin resources are typically scarce and sporadic. In a traditional rural environment and among traditional hunter-gatherers, humans continuously receive vast amounts of dormant and slow-growing bacteria from outdoor environment, such as forest soils.

20 In a modern urban society, the supply of these slow-growing, non-culturable bacteria is often limited as typically used landscaping and gardening materials either have a poor microbial community or they are designed for optimal growth of decorative plants.

A well-known raw material used to manufacture gardening materials is humified peat. 25 In peat, bacterial abundance is low. When peat is fertilized and mixed with inorganic sieved mineral soil particles or other substances, the bacterial abundance, and in particular abundance of non-culturable bacteria, remains lower than is found in natural forest soils. Another important raw material used in gardening is animal dung where microbial abundance is high but microbial community is very different from natural forest soils. When peat and animal dung or human faeces are combined and composted, microbial community of the composted material is reminiscent of microbial community in dung / faeces.

For these reasons, microbial communities in urban environments are different from those encountered in natural forest environments. Microbial communities in urban environments have either a lower bacterial abundance, such as in peat-based gardening materials and landscaping materials comprising mostly mineral soil particles, or they have a bacterial community that is qualitatively different from the bacterial community in forest soils, examples of such gardening materials comprise dung-based and composted products.

Today, non-infectious diseases are a huge and economically important global problem in urban areas. These diseases cover autoimmune diseases and many allergies, dysbiosis, irritable bowel syndrome and even certain mental disorders. In many of them, such as immune systems disorders, human microbiome is different from healthy controls, and consequently the diseases are associated with the levels of proinflammatory and immunoregulatory cytokines, examples of the latter are interleukin-10 and transforming growth factor beta.

The imbalance of human microbiome in urban areas is currently being treated using probiotics that contain a single or a few fast-growing, culturable bacterial strains. The benefits of probiotics cover reduced probability of diarrhea and potentially also less severe or less probable otitis media, helicobacterial infection, depression and alcoholic liver diseases. In addition, the currently available treatments of immune related diseases comprise drugs, prebiotics that are chemicals and purified allergens. Notably, there have been no attempts to systematically import the slow-growing, partially dormant microbial community into urban outdoor environments using products manufactured for this purpose, in order to expose urban subjects to a diverse microbial community.

SUMMARY

The authors have surprisingly found out that it is possible to manufacture landscaping and gardening materials that comprise forest soil microbial community both qualitatively and quantitatively, or that comprise microbial community that is both qualitatively and quantitatively highly reminiscent of forest soil microbial community. As forest soil, particularly its near-surface upper layers, and many other heterogeneous microenvironments within forests, such as surface of needles, moss layer and bark surface, comprise a rich community of dormant and slow-growing bacteria, the materials comprising those microenvironments can be mixed with existing landscaping and gardening materials, without destroying the dormant or slow-growing cells. As a result, Hellinger distance (i.e. bacterial community dissimilarity) to forest soil bacterial community can be kept small and bacterial abundance high. The dormant and slow-growing cells will thereafter persist and reproduce in the new landscaping and gardening materials according to the current invention. As the new landscaping and gardening materials according to the current invention comprise numerous heterogeneous and sporous microenvironments, the inactive and slow-growing microbes have a high probability of survival over a long period of time, thereby being able to produce immunomodulatory effect to urban dwellers for a long time when such a material is used in urban landscaping or gardening.

The outcome of contacts between urban subjects and the landscaping and gardening materials according to the current invention is altered skin and stool microbial community of the urban subjects. In addition, providing that the exposure is sufficient and preferably on a daily basis, the gardening and landscaping materials according to the current invention have the capacity to modulate the immune response of a human subject.

Without being bound to any theory, it is known that the coverage of forests and agricultural land is associated with a reduced risk of getting one of those diseases (Hanski et al. 2012). The association has been observed to be stronger in case of forested areas (Hanski et al. 2012, see also supplement 1 in Hanski et al. 2012). In parallel, it has been observed that particulary Bacteroidetes, Proteobacteria and Gammaproteobacteria play a significant role in etiology of the non-infectious diseases. In addition, other classes within Proteobacteria, and Acidobacteria, Actinobacteria, Firmicutes and Parcubacteria may play a similar role. However, prior publications have not been able to identify the necessary criteria that can be used to select a microbiologically rich material which can be used to manufacture landscaping or gardening material which has beneficial immunomodulatory effects of forest soil which can produce immunomodulatory effects. According to a first aspect is provided a method of manufacturing immunomodulatory landscaping material comprising: a. providing bulk landscaping material comprising either a low bacterial abundance of 2 000 000 000 16S sequences per g wet weight or less, and/or a bacterial community having Hellinger distance of 1 .10 or more from forest soil, Bacteroidetes community having Hellinger distance of

0.99 or more from forest soil, Proteobacterial community having Hellinger distance of 1 .05 or more from forest soil, and/or Gammaproteobacterial community having Hellinger distance of 1 .10 or more from forest soil; b. providing microbiologically rich material comprising a bacterial community having abundance of at least 400 000 000, preferably at least

2 500 000 000 16S sequences per g wet weight, and/or Hellinger distance of 1 .00 or less from forest soil, Bacteroidetes community having Hellinger distance of 0.93 or less from forest soil, Proteobacterial community having Hellinger distance of 0.91 or less from forest soil, and/or Gammaproteobacterial community having Hellinger distance of

1 .01 or less from forest soil; and c. mixing a with b.

According to a second aspect is provided an immunomodulatory landscaping material manufactured using the method of the first aspect. According to a third aspect is provided immunomodulatory landscaping material having a Hellinger distance of 1 .08 or less from forest soil in case of the bacterial community; a Hellinger distance of 0.97 or less from forest soil in case of the Bacteroidetes community; a Hellinger distance of 1 .03 or less from forest soil in case of the Proteobacterial community; and a Hellinger distance of 1 .07 or less from forest soil in case of the Gammaproteobacterial community. According to a fourth aspect is provided the immunomodulatory landscaping material of the second aspect for use in strengthening immune system of a subject.

In an embodiment the use is medical use. In another embodiment the use is nonmedical use. According to a fifth aspect is provided use of the landscaping material for growing edible plants.

According to a sixth aspect is provided a gardening material comprising the immunomodulatory landscaping material.

According to another aspect is provided a turf system comprising a plurality of turf units disposed on an underlying surface in proximity to each other to form a turf unit array, the turf units containing the immunomodulatory landscaping material in which a plurality of turf plants is growing.

According to another aspect is provided an immunomodulatory landscaping material having abundance of at least 400 000 000, preferably at least 2 500 000 000, 16S sequences per g wet weigh, and richness of at least 500, preferably at least 600, 700, 800, 900 or 1000; and optionally diversity of at least 100, preferably at least 150, 200, 250 or 300. In an embodiment richness and diversity are as determined as in Example 4.

BRIEF DESCRIPTION OF THE FIGURES

Fig 1 . NMDS figure of two different immunomodulatory gardening materials (freeze- dried and mixture), traditional organic gardening materials with bacterial abundance of less than 2 000 000 000 (product.Conif), other currently available organic gardening materials (Product. nonConif), natural forest soil samples and raw materials of coniferous origin.

Fig. 2. OTU richness and bacterial diversity in hands after touching a bulk landscaping material (Sand) and the same material enhanced with microbiologically rich material. The graphs show the results of obtained in Example 4. ^* = significant difference between treatments

SEQUENCE LISTINGS

SEQ ID NO: 1 : forward primer 505F

SEQ ID NO: 2: reverse primer 806R

SEQ ID NO: 3: reverse primer pE

SEQ ID NO: 4: reverse primer pF

SEQ ID NO: 5: primer pA 1

SEQ ID NO: 6: primer pA 2

SEQ ID NO: 7 primer pA 3

SEQ ID NO 8: primer pD' 1

SEQ ID NO 9: primer pD' 2

SEQ ID NO: 10: primer pD' 3

SEQ ID NO: 1 1 : primer for sequencing pA

SEQ ID NO 12: primer for sequencing pD'

DETAILED DESCRIPTION OF THE INVENTION

As used herein, the term "comprising" includes the broader open meanings of "including", "containing", and "comprehending", as well as the narrower closed meanings of the expressions "consisting of and "consisting only of. The term immunomodulatory is multifaceted in the context of this application and it includes at least the following aspects: In one aspect it refers to the stimulation of the immune response to the foreign and harmful materials such as pathogens. It also refers to the overall enhancement of the health, function and potency of the immune system. It also refers to the training of the immune system to response appropriate and healthy ways for different stimuli and to avoid unhealthy pathological responses. It also covers immunoregulatory and immunostimulatory aspects to tune the immune response in a healthy way and to avoid unhealthy responses. In one aspect it also refers to the maintaining of the healthy status of immune system and immune response or to slowing down the decline of the immune system and immune response for example in the cases of immune system affecting diseases and aging.

Mineral soil materials comprise silicates such as olivine, epidite, melilite, tourmaline, pyroxene, amphibole, micas, clays, quartz, feldspars and zeolites. Examples cover chips, macadam, sand, silt.

The term operational taxonomic unit (shortened as OTU) refers to clusters of 16S or 18S small subunit rRNA gene similarity and it is used as an approximation of microbial taxa (Schmidt et al. 2014). The term richness refers to the total number of OTUs per sample which is processed as follows: Samples are stored in deep freezer (<-70°C) before DNA extraction and processed for MiSeq sequencing mainly following Veach et al. (2015). For each sample, approximately 0.25 g soil is used for DNA extraction. Three sample replicates are extracted and pooled before sequencing. Total DNA is extracted from samples using PowerSoil® DNA Isolation Kit (MoBio Laboratories, Inc., Carlsbad, CA, USA) according to the manufacturer's standard protocol. DNA is checked with agarose gel (1 .5 %) electrophoresis (120 V, 30 min). Total DNA concentration is measured e.g. with Quant-iT™ PicoGreen® dsDNA reagent kit (Thermo scientific, MA, USA). The DNA concentration is adjusted to 0.35-0.4 ng/μΙ to each sample. DNA is analyzed for bacterial (16S) communities using a two-step PCR approach to avoid a 3'-end amplification bias resulting from the sample-specific DNA tags (Berry et al. 201 1 ). The V4 region within the 16S ribosomal RNA (rRNA) gene is amplified by primary PCR as triplicates using 505F and 806R primers (Caporaso et al. 2012). Primary PCR is carried out in a reaction mixture (reaction volume 50 μΙ) consisting of 1 μΙ each of 10 mM deoxynucleoside triphosphates (dNTPs; Thermo scientific, MA, USA) 5 μΙ forward primer 505F (10 μΜ; 5' -GTGCCAGCMGCCGCGGTAA-3') and 5 μΙ reverse primer 806R (10 μΜ; 5'- GGACTACHVGGGTWTCTAAT-3'), 0.5 μΙ 2 U/μΙ Phusion Green Hot Start II High-Fidelity DNA polymerase (Thermo scientific, MA, USA), 10 μΙ 5x Green HF PCR buffer (F-537), 5 μΙ template DNA and 23,5 μΙ sterile water. The PCR reaction is run in a thermocycler as follows: initial denaturation at 98 °C for 5 min, followed by 25 cycles with denaturation at 94 °C for 1 min, annealing for 10 sec at 50 °C and extension for 1 min at 72 °C, and then a final extension at 72 °C for 10 min. DNA is detected with agarose gel (1 .5 %) electrophoresis (120 V, 1 h). The PCR products is purified using e.g. Agencourt AMPure XP solution (Beckman Coulter Ins.) to reduce carryover of primary PCR primers. Triplicates of the cleaned amplicons are pooled and diluted 1 :5. Cleaned and diluted primary PCR products are targeted in the secondary PCR (TagPCR). Reaction mixture to the TagPCR is equal to above except reverse primer include a 12 bp unique Multiplexing Identifier tag (MID-806R). Amplification program is the same as above except there are only seven cycles. TagPCR products are detected on agarose gel (1 ,5 %) electrophoresis (120 V, 1 h), purified with Agencourt AMPure, pooled and the DNA concentration is measured with PicoGreen. The sequencing is performed using lllumina MiSeq platform with a 2x300bp version 3 kit sequencing kit according to manufacturer's protocol. The GeneRead DNA Library I Core Kit (Qiagen, catalog # 180432) is used to ligate lllumina's TruSeq adapters to amplicons. The sequence processing protocol mainly follows the pipeline suggested by Schloss et al. (201 1 ) and Kozich et al. (2013). The paired sequences contained in reverse and forward fastq files are aligned into a contig. The resulted library is trimmed and screened to remove any mismatches with primer or DNA-tag sequences, ambiguous bases and homopolymers larger than 8 bp long. Sequences are aligned using Mothur version of SILVA bacterial reference sequences (version 102; Pruesse et al. 2007) and the sequences which are not aligned to a reference alignment of the correct sequencing region are removed. The samples having more than 20 000 sequences are rarefied to 20 000 sequences. At this point of sequence processing, the samples having less than 20 000 sequences are retained without rarefying. Unique sequences and their frequency in each sample is identified, and then, almost identical sequences (>99 % similar) are preclustered to minimize sequencing errors (Huse et al. 2010) and screened for chimeras (UCHIME, Edgar et al. 201 1 ) using the abundant sequences as a reference. The chimeric sequences are removed. The sequences are classified using Mothur version of Bayesian classifier (Wang et al. 2007) with the RDP training set version 9 (Cole et al 2009). Sequences that are classified as Mitochondria, Chloroplast, Archaea, Eukaryota or unknown are removed. Operational taxonomic units (OTUs) are assigned at 97 % identity. OTUs are clustered using nearest neighbor algorithm in Mothur where each of the sequences within an OTU are at most 3% distant from the most similar sequence in the OTU (https://mothur.org/wiki/Cluster, accessed 5th December 2016). Rare OTUs that are represented with 10 or fewer sequences in the whole data are removed. The possible contamination found in negative controls will be taken into account by adjusting the number of sequences in each OTU based on what is found in controls. This is done by taking into account the initial rarefaction to 20 000 sequences of some samples. First, the sample wise proportions for each OTU are calculated. Second, the expected number of sequences for each OTU without the initial rarefaction is calculated using the proportions and the total number of sequences in each sample prior the initial subsampling. Third, for each OTU the number of sequences detected in control is subtracted from the samples and negative values are changed to zeros. Fourth, the proportion of sequences removed from each sample is detected and this proportion of sequences is removed from the final data. Alternatively, the initial rarifying to 20 000 sequences can be skipped and in this case contamination will be removed by directly subtracting the number of sequences found from controls from each OTU in each sample. The sequences are classified using the Mothur version of Bayesian classifier (Wang et al. 2007) with the RDP training set version 9 (Cole et al 2009) and a consensus taxonomy for each OTU is generated. Finally, all the samples are rarefied to equal number of sequences not less than 1400.

The term whole bacterial community refers to all OTUs in a sample that has been collected and processed similarly as explained above. The term Proteobacterial community refers to a subset of whole bacterial community including only those OTUs that are assigned to Phylum Proteobacteria according to the consensus taxonomy.

The term Bacteroidetes community refers to a subset of whole bacterial community including only those OTUs that are assigned to Phylum Bacteroidetes according to the consensus taxonomy. The term Gammaproteobacterial community refers to a subset of whole bacterial community including only those OTUs that are assigned to Class Gammaproteobacteria according to the consensus taxonomy.

The term Hellinger distance refers to distance between samples xi and X2 calculated 5 as follows (Rao 1995; Legendre & Legendre 2012):

, where yi is the frequency in column (i.e. OTU) j in row (i.e. sample) 1 and yi+ is the sum of frequencies in column j. When the communities in samples 1 and 2 are exactly the same, the distance is 0 and when the samples do not share any common 10 OTUs, the distance gets value of V2.

Other commonly used community distance metrics are, for instance Bray-Curtis distance. Unlike Bray-Curtis distance, Hellinger distance takes into account varying total sample sizes. Hellinger distance was chosen also because it is better suited for community ecological studies (Legendre & Gallagher 2001 ).

15 The term abundance refers to the total number of 16S or 18S gene copies per g wet weight. The abundance is detected using quantitative PCR (e.g. Light Cycler 96 Quantitative real-time PCR machine (MJ Research, MA, USA)) with forward primer pE 5 ^' -AAA CTC AAA GGA ATT GAC GG-3 ^* and the reverse primer pF 5 ^' -ACG AGC TGA CGA CAG CCA TG-3 ^* (Oqvist et al. 2008). All samples are run in triplicates in

20 20 μΙ reactions containing 10 μΙ 2x PowerUp SYBR Green Master Mix (Thermo scientific, MA, USA), 0.2 μΙ 20 mg/ml BSA, 0.5 μΙ of each primer (10 μΜ), and the sample template. A standard curve is included in every run to allow quantitation of the number of bacterial 16S copies present in the original sample. The q-PCR run is as follows: initial denaturation at 95 °C for 2 min, followed by 40 cycles of

25 denaturation at 95 °C for 10 s, annealing for 20 sec at 53 °C and extension for 30 s at 72 °C.

Forest soil refers to soil in a forest. According to United Nations Framework Convention on Climate Change (UNFCCC 2002), a forest is a minimum area of land of 0.05-1 .0 hectares with tree crown cover (or equivalent stocking level) of more than 10-30 per cent with trees with the potential to reach a minimum height of 2-5 meters at maturity in situ. A forest may consist either of closed forest formations where trees of various storeys and undergrowth cover a high proportion of the ground or open forest. Young natural stands and all plantations which have yet to reach a crown density of 10-30 per cent or tree height of 2-5 meters are included under forest, as are areas normally forming part of the forest area which are temporarily unstocked as a result of human intervention such as harvesting or natural causes but which are expected to revert to forest. The term turf comprises sod and any other kind of transferable lawn, not peat or forest floor surface.

In an embodiment the bulk landscaping material has poor microbiological diversity and richness and it comprises mostly mineral soil material.

In an embodiment the bulk landscaping material has poor bacterial abundance of less than 2 000 000 000 and it comprises mostly peat.

In an embodiment the bulk landscaping material has poor bacterial abundance of less than 100 000 000 and it comprises mostly mineral soil material. In an embodiment the material is sand.

In an embodiment the bulk landscaping material is mineral soil comprising a bacterial community having bacterial abundance of less than 400 000 000 16S sequences per g wet weight and/or a bacterial community having Hellinger distance of 1 .02 or more from forest soil; Bacteroidetes community having Hellinger distance of 0.95 or more from forest soil; Proteobacterial having Hellinger distance of 0.93 or more from forest soil, and Gammaproteobacterial community having Hellinger distance of 1 .03 or more from forest soil.

In an embodiment the bulk landscaping material is agricultural soil.

In an embodiment the mineral soil is agricultural field soil.

In an embodiment pathogens are removed, or their amount is reduced, in the bulk landscaping material. In an embodiment the mixing of a. with b. is carried out in amounts and to an extent to reach a Hellinger distance of 1 .08 or less from forest soil in case of the bacterial community of the resulting immunomodulatory landscaping material; a Hellinger distance of 0.97 or less from forest soil in case of the Bacteroidetes community of the resulting immunomodulatory landscaping material; a Hellinger distance of 1 .03 or less from forest soil in case of the Proteobacterial community of the resulting immunomodulatory landscaping material; and a Hellinger distance of 1 .07 or less from forest soil in case of the Gammaproteobacterial community of the resulting immunomodulatory landscaping material. In an embodiment mixing is carried out to obtain immunomodulatory landscaping material which has richness of at least 500, preferably at least 600, 700, 800, 900 or 1000; and optionally diversity of at least 100, preferably at least 150, 200, 250 or 300.

In an embodiment the microbiologically rich material has a richness of at least 500, preferably at least 600, 700, 800, 900 or 1000. In an embodiment the richness has a unit of number of OTUs per sample.

In an embodiment the microbiologically rich material has a diversity (Simpson's diversity index) of at least 100, preferably at least 150, 200, 250 or 300, in bacterial 16S rRNA extracted from 0.25 g soil. The term Simpson diversity index refers to inverse Simpson's index i.e. Simpson's Reciprocal Index 1 / D (Simpson 1949), in which

D = Σ(η,(η,-\))/(Ν(Ν -I)) where n, is the number of individuals in species i and N is the total number of individuals in the community.

In an embodiment the quality of the microbiologically rich material is monitored. Monitoring can be carried out by assessing microbiological richness, abundance and/or diversity.

In an embodiment the microbiologically rich material comprises powdered, crushed, extracted or whole needles, bark, leaves, leaf litter, forest floor, forest soil, moss, Sphagnum moss, peat belonging to humification classes H1-H4 on the scale of von Post (Wust et al. 2003), straw, cones, inflorescence, seeds, capsule or other organic forest material containing non-culturable forest microbial community, or mining material rich in humic and fulvic acids.

In an embodiment the microbiologically rich material, and optionally the immunostimulatory landscaping material, is dry. Drying can be carried out using methods known in the art, such as air-drying or freeze-drying. In an embodiment mixing with the bulk landscaping material is carried out after drying.

In an embodiment the method comprises processing the immunomodulatory landscaping material into the form of a turf unit. In an embodiment the bulk landscaping material comprises turf.

In an embodiment the bulk landscaping material comprises artificial turf.

In an embodiment the bulk landscaping material comprises turf, and the microbiologically rich material comprising immunomodulatory components is added to, or used on, the turf as an extract, powder, crushed or whole plant parts. In another embodiment the bulk landscaping material is mixed with the microbiologically rich material before seeding of the turf, at some point before transportation, or at its final destination.

In an embodiment the forest soil is soil of forest according to UNFCCC 2002.

In an embodiment the method comprises a step of controlling the level of pathogens. In an embodiment controlling is by removing or killing pathogenic bacteria in the bulk landscaping material.

In an embodiment the bulk landscaping material comprises mineral material and the microbiologically rich material comprising immunomodulatory components are added to the mineral material as an extract, powder, or crushed or whole plant parts or as a supplement after mixing.

In an embodiment the mixing results in a permanent microbial community.

In an embodiment the microbiologically rich material is added periodically to the immunomodulatory landscaping material. In an embodiment the addition is carried out 1 -3 times per growing season. The addition strengthens the microbiologically rich bacterial community, and increases microbiological richness of the landscape.

In an embodiment the microbiologically rich material is used to enrich microbiologically poor urban environment comprising bulk landscaping material. In an embodiment the bulk landscaping material comprises composted material, turf, green roof, mineral material, chips, macadam, sand, silt, clay and any other material comprising mostly of silicate particles.

In an embodiment the immunomodulatory landscaping material is immunomodulatory turf, and preferably the Hellinger distance values from forest floor are 1 .00 or less for the whole bacterial community, 0.95 or less for Bacteroidetes community, 1 .00 or less for Proteobacterial community, and 1 .00 or less for Gammaproteobacterial community.

In an embodiment the immunomodulatory landscaping material is immunomodulatory mineral material, and preferably the preferred Hellinger distance values are 1 .06 or less for the whole bacterial community, 0.95 or less for the Bacteroidetes community, 1 .02 or less for the Proteobacterial community, and 1 .06 or less for the Gammaproteobacterial community.

In an embodiment the immunomodulatory landscaping material has abundance of at least 400 000 000, preferably at least 2 500 000 000, 16S sequences per g wet weigh, and richness of at least 500, preferably at least 600, 700, 800, 900 or 1000; and optionally diversity of at least 100, preferably at least 150, 200, 250 or 300.

In an embodiment in the immunomodulatory landscaping material the percentage (per dry weight) of inorganic material is more than 50 %, preferably more than 90 %.

In another embodiment the immunomodulatory landscaping material comprises 1 - 90% microbiologically rich material, such as 1 -50% or 1 -20%, 5-50% or 5-20%. In an embodiment the bulk landscaping material is mineral soil, such as sand, and mixing comprises mixing at least 50% (w/w wet weight) of the mineral soil with the microbiologically rich material. In another embodiment at least 85% of mineral soil is mixed with the microbiologically rich material. In yet another embodiment pathogens are removed or substantially removed from the mineral soil before mixing.

In an embodiment the Hellinger distance of the immunomodulatory landscaping material and the microbiologically rich material are smaller than in the bulk landscaping material for Acidobacteria, Actinobacteria, Firmicutes or Parcubacteria. In another embodiment the Hellinger distance is 1 , preferably 0.8.

In an embodiment the value of Hellinger distance of the immunomodulatory landscaping material is below the set threshold values presented in claim 6 in case of the whole bacterial community and either Proteobacteria or Bacteroidetes.

In an embodiment the value of Hellinger distance of the immunomodulatory landscaping material is below the set threshold values presented in claim 6 in case of Proteobacteria and Bacteroidetes but not in the whole bacterial community.

In an embodiment the value of Hellinger distance of the immunomodulatory landscaping material is below the set threshold values presented in claim 6 in case of Gammaproteobacteria and either Proteobacteria or Bacteroidetes but not in the whole bacterial community.

In an embodiment the value of Hellinger distance of immunomodulatory landscaping material is below the set threshold values presented in claim 6 in case of Gammaproteobacteria and the whole bacterial community.

In an embodiment the value of Hellinger distance of immunomodulatory landscaping material is below the set threshold values presented in claim 6 in case of one of the bacterial taxons mentioned in those claims.

In an embodiment the immunomodulatory landscaping material is in the form of an immunomodulatory turf, immunomodulatory green roof, immunomodulatory mineral material, immunomodulatory chips, immunomodulatory macadam, immunomodulatory sand, immunomodulatory silt, immunomodulatory clay and any other immunomodulatory material comprising mostly of mineral soil particles, and composted materials used for urban gardening. In an embodiment the immunomodulatory landscaping materials is for growing edible plants.

In an embodiment the microbiologically rich material has Hellinger distance values of 0.72 or less for the whole bacterial community, 0.69 or less for the Bacteroidetes community; 0.67 or less for the Proteobactenal community; and 0.72 or less for the Gammaproteobacterial community.

In an embodiment the preferred Hellinger distance of the microbiologically rich material are 0.99 or less for the whole bacterial community, 0.77 or less for Bacteroidetes community, 0.95 or less for Proteobactenal community, and 0.99 or less for Gammaproteobacterial community.

In an embodiment the microbiologically rich material comprises or is derived from forest floor, comprising soil.

In an embodiment in the microbiologically rich material the richness of the whole bacterial community is at least 182, preferably more than 227; richness of Bacteroidetes community is at least 26, preferably more than 34; richness of Proteobacterial community is at least 60, preferably more than 65; and richness of Gammaproteobacteria is at least 18, preferably more than 21 .

In an embodiment in the bulk landscaping material has a richness of the whole bacterial community is less than 182; richness of Bacteroidetes community is less than 26; richness of Proteobacterial community is less than 50; and richness of Gammaproteobacterial community is less than 18.

In an embodiment the immunomodulatory material or the immunomodulatory gardening material is turf or green roof.

In another embodiment an inoculum of the edible plant is enriched with immunomodulatory material.

An advantage of the present invention is that the microbiome of subjects living in urban, microbiologically poor, environment can be returned closer to that encountered in rural environments. Because of the change in the microbiome, immune system is strengthened and immune system disorder can be avoided. Thus, the immunomodulatory landscaping material prevents autoimmune diseases and disorders of immune system.

The present materials are suitable for use in different landscaping and gardening constructions. As an example, they can be used in parks, gardens, yards, sports fields, pitches, golf links, playgrounds, paths, and roads. The materials are also suitable to be added on existing constructions.

In an embodiment the immunomodulatory landscaping material or the immunomodulatory gardening material is diluted before use. Dilution can be made by mixing the material with a third substance, such as water or an industrial by-product. In an embodiment the bulk landscaping material or a gardening material is first mixed with immunomodulatory materials to form the immunomodulatory landscaping material or the immunomodulatory gardening material, and thereafter the two materials are separated by extraction, wind instrument or sieving. As a result, the immunomodulatory properties of immunomodulatory materials have been transferred to the novel landscaping and gardening materials.

In an embodiment pathogens of the immunomodulatory landscaping materials are controlled. Controlling may comprise studying presence of a single pathogenic species or analysing the total number of sequences in pathogenic genera. An acceptable level for the immunomodulatory landscaping material is a value which is lower than in everyday living environment in urban areas.

In an embodiment the immunomodulatory landscaping material is a homogeneous or substantially homogeneous mixture of the bulk landscaping material and the microbiologically rich material. Such a mixture is advantageous in that the non- culturable bacteria are efficiently spread over the entire material, and the local concentration of pathogens is reduced.

Examples Example 1. Gardening material comprising Sphagnum moss.

Immunomodulatory gardening materials comprising non-culturable microbial community, their raw materials, and natural organic soils were compared to study community composition of bacterial phylum Bacteroidetes. Methods

Bulk gardening materials were divided to two separate groups, those that did not comprise (called jointly as Product. nonConif, n = 7), and those that comprised humified peat or pieces of bark (called jointly as Product. Con if, n = 7). Organic materials derived from nature consisted of Sphagnum mosses of different geographic origin (3 samples), peat of different geographic origin (2 samples) and two types of grated bark (called jointly raw.mat.Conif). Pieces of natural forest soil (1 m ² each) were taken from two sources of different geographic origin. They were cut from forest and transferred immediately to laboratory where sampling was made. The gardening materials and organic materials were mixed thoroughly before sampling. Samples were taken from 5 separate spots in each material. Distance between spots was at least 3 cm. Sample size was 2 g. Natural forest soils were sampled as follows: sample size 2 g, sampling depth 5-20 mm, 5 subsamples per soil, the distance between sampling points was at least 10 cm, subsamples were pooled and mixed thoroughly before molecular analyses. Two types of immunomodulatory gardening materials were manufactured. Sieved immunomodulatory gardening material (called as mixture in Fig 1 ) was manufactured by mixing crushed and air-dried (24 h) Sphagnum moss with composted soil materials. The general ingredients for these soil materials were various compositions of composts (raw materials cattle dung, horse dung, chicken dung, deciduous leaf litter, plant debris, horticultural peat, sludge, fine mineral soil such as silt as well as crushed tree bark mulch). The immunomodulatory gardening material consisted of four major ingredients (three types of composted soil materials and the moss) and eight minor ingredients (peat and different composted soil materials). Before the materials were combined and mixed, the major and minor components were sieved with 0 5 mm and 0 2 mm sieves, respectively, except for the moss that was dried, crushed and sieved with 0 2 mm sieve and mixed. The combined ratio for the test material was 4:1 :0.5 for each major composted materials, moss and each minor material, respectively. Sieved immunomodulatory gardening material consisted of two separate mixing batches that were not manufactured simultaneously. Altogether eight samples were taken. Four samples were taken from each batch of the sieved immunomodulatory gardening material. As sieved immunomodulatory gardening material was divided into 5 I buckets before sampling, each sample was taken from a separate bucket.

Freeze dried gardening material (called as freeze-dried in Fig 1 ) was manufactured by first taking approximately 1 liter of sieved immunomodulatory gardening material in a clean plastic container. Ultra-pure Milli-Q water was poured slowly into the container and mixed thoroughly until the soil was saturated (i.e. water started dripping when the wet soil was held in hand). Approximately 800 ml water was needed for saturation. The soil water mixture was kept inside a laminar hood at room temperature for 4 hours covered with a lid but holes on the side walls of the container allowed adequate air circulation. The soil-water mixture was then hand-squeezed using sterilized laboratory gloves over an ethanol-cleaned 250 μιτι sieve placed above another sterile plastic container. The extract was collected in separate 50 ml Falcon tubes. All the samples were frozen at -20 ^° C prior to freeze-drying. Approximately 48 hours was needed for the freeze drying process to complete. Three samples of the freeze dried immunomodulatory gardening material were used for extraction and sequencing.

Sample preparation, DNA extraction, sequencing, and for the most part, also sequence processing, were performed as described in pages 6-8. There was two exceptions in sequence processing: first, all the OTUs found in control samples were totally removed from the data, and second, the data was rarefied to 748 sequences because this was the minimum number of sequences per sample.

Non-metric dimensional scaling (NMDS) was used to visualize the community composition within bacterial Phylum Bacteroidetes. NMDS ordination was done using metaMDS-function in R package vegan and Bray-Curtis-distance. Results

Traditional gardening materials formed two loose groups of samples in the NMDS ordination and some of the samples - particularly those without raw materials originating in coniferous forests - were rather distant from the natural forest soil samples as well as organic raw materials. However, the samples of sieved immunomodulatory gardening material and freeze dried immunomodulatory gardening material formed a tight group of samples which was located close to the natural forest soil samples as well as organic raw materials. As currently available gardening materials that comprise raw materials of forest origin have a very low bacterial abundance (see example 3), and as other current gardening material have a distinctly different Bacteroidetes community from forest soil samples, the technical effect is that it is possible to manufacture organic gardening materials where Bacteroidetes community is reminiscent of Bacteroidetes community in forest soils. This is an important finding as forest microbial community has been associated with positive health effects. Another technical effect is that the community composition of Bacteroidetes in gardening materials can be changed to resemble the composition of Bacteroidetes community of natural forest soil. As a results, urban subjects can expose them to immunomodulatory gardening materials outdoors in urban environments. When this happen frequently enough, the probability of many non- infectious diseases decreases as compared to a situation where the outdoor exposure to immunomodulatory gardening materials is missing.

Results are shown in Fig. 1 .

Example 2. Bacterial abundance of currently existing mineral soil materials manufactured for landscaping. Bacterial abundance of currently existing mineral materials were measured. In addition, the bacterial abundance of the sieved immunomodulatory gardening material described in example 1 was measured. The currently existing gardening materials were provided by the manufacturers and they can be bought as retail products. As seen in Table 1 , all of them either have a too low bacterial abundance (16S copies per gram wet weight) and their total bacterial community [H(tot)], Bacteroidetes community [H(Bact)], Proteobacterial community [H(Prot)] and Gammaproteobacterial community [H(G-prot)] composition is distant from those communities in coniferous forest soil. The technical effect is that currently available mineral soil materials targeted for landscaping are not suitable for immune modulation. Another technical effect is that - based on example 1 - it may become possible to design immunomodulatory landscaping materials comprising mostly of mineral soil materials. Preferably microbiologically abundant and diverse organic materials are fully mixed to the current landscaping materials. Table 1. Bacterial abundance (16S sequences per gram wet weight) in several currently available mineral soil materials targeted for landscaping or gardening, and the sieved immunomodulatory gardening material prepared in example 1 .

Example 3. Bacterial abundance and Hellinger distance of currently existing gardening materials from forest floor

Bacterial abundance and Hellinger distance of currently existing gardening materials from forest soil samples were measured. In addition, we prepared crushed and air- dried (24 h) moss and did the same analyses. The currently existing gardening materials were provided by the manufacturers and they can be bought as retail products. As seen in Table 2, all of them either have a too low bacterial abundance (16S copies per gram wet weight) or their total bacterial community [H(tot)], Bacteroidetes community [H(Bact)], Proteobacterial community [H(Prot)] and Gammaproteobacterial community [H(G-prot)] composition is distant from those communities in coniferous forest soil. Therefore, their suitability for immune modulation is of minor importance. As shown in Table 2, we were able to manufacture immunomodulatory material for gardening materials by air-drying (24 h) and carefully crushing Sphagnum moss. In the novel material, Hellinger distances were low as compared to forest soil (< 0.73 in all cases) and bacterial abundance was high (» 2 000 000 000). Table 2. Bacterial abundance (16S copies per gram wet weight), and Hellinger distances of the whole bacterial community [H(tot)], Bacteroidetes community [H(Bact)], Proteobacterial community [H(Prot)] and Gammaproteobacterial community [H(G-prot)] in currently available gardening materials + crushed and air- dried Sphagnum moss as compared to forest soil.

This is an impactful revelation as lack of diverse and abundant microbial exposure has been linked to numerous non-infectious diseases including inflamed bowel systems, type 1 diabetes, and Crohn's disease. A technical effect is that the use of the immunomodulatory materials in manufacturing gardening and landscaping materials according to the current invention can lead to an increase in microbial abundance and a decrease in Hellinger distance as compared to forest soil. Another technical effect thus is that the outdoor use of the immunomodulatory gardening and landscaping materials according to the current invention can contribute to an increase in microbial diversity and abundance that urban subjects are exposed to. Example 4. Effect of bulk and enhanced landscaping materials on skin bacterial community Three types of bulk landscaping material were provided (safety sand, sieved sand and playground sand) from retail markets.

The materials contained > 99 % of mineral soil particles, particularly sand.

Their diversity and richness were measured and observed to be low and their bacterial abundance was below 100 000 000 16S sequences per g wet weight.

Bulk landscaping materials were mixed with freeze-dried, microbiologically diverse material comprising a bacterial community having abundance of 5 000 000 000 16S sequences per g wet weight, and pathogen level was below levels found in normal living environment in urban settings, and Hellinger distance of less than 1 .00 from forest soil, Bacteroidetes community having Hellinger distance less than 0.93 from forest soil, Proteobacterial community having Hellinger distance less than 0.91 from forest soil, and Gammaproteobacterial community having Hellinger distance less than 1 .01 from forest soil;

The ratio was 1 part microbiologically rich material mixed thoroughly to 9 parts of bulk landscaping material.

Five volunteers were randomized to touch the materials with second and third finger. Volunteers washed their hands with soap just before starting the experiment.

Five volunteers dipped a finger tip in bulk and another finger tip in microbiologically enhanced but otherwise similar landscaping material. Each material was touched four times, i.e., there were two separate pairs of each bulk and each enhanced material.

Touching lasted for 20 seconds.

Cotton wool stick was used to take microbial samples.

The volunteers followed the following protocol during the experiment: 1 . Wash your hands with soap 20 s.

2. Roll your finger in control tube 20 s. 3. Don't touch anything with your exposed finger and roll another finger in test tube 20 s.

4. Assistant takes swap samples from bulk and microbiologically enhanced fingers (n=2), 5 strokes from finger head to lowest joint. Skin swap samples were stored in deep freezer (<-70°C) in tubes containing Tween 20 (MP Biomedicals) (0,1 %) + NaCI (0,1 M, J.T.Baker ) before DNA extraction. Total DNA was extracted from samples using PowerSoil® DNA Isolation Kit (MoBio Laboratories, Inc., Carlsbad, CA, USA) according to the manufacturer's standard protocol. The swap and the liquid (approximately 650 μΙ Tween + NaCI) were transferred to the PowerBead tube for a homogenization and lysis procedure. DNA was checked with agarose gel (1 .5 %) electrophoresis (120 V, 30 min). The amplification was done using a two-step PCR protocol. An approximately 500 bp fragment covering the V1 - V3 variable regions of the 16S rRNA gene was amplified and using primers pA (mixture of SEQ ID NO: 5 5'-AGAGTTTGATCMTGGCTCAG- 3', SEQ ID NO: 6 5'-TAGAGAGTTTGATCMTGGCTCAG-3', SEQ ID NO: 7 5'- CTCTAGAGTTTGATCMTGGCTCAG-3') and pD' (mixture of SEQ ID NO: 8 5'- GTATTACCGCGGCTGCTG-3', SEQ ID NO: 9 5'-CGTATTACCGCGGCTGCTG-3', SEQ ID NO: 10 5'-TAGTATTACCGCGGCTGCTG-3') (Edwards et al. 1989). The primers had 5' overhangs for lllumina sequencing SEQ ID NO: 1 1 5'- ATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT-3' for pA and SEQ ID NO 12 5'- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3' for pD'. The PCR protocol was as described in Koskinen et.al. (201 1 ). Primary PCR was carried out in a reaction mixture (reaction volume 50 μΙ) consisting of 1 μΙ each of 10 mM deoxynucleoside triphosphates (dNTPs; Thermo scientific, MA, USA), 5 μΙ forward primer pA (10 μΜ) and 5 μΙ reverse primer pD (10 μΜ) , 0.5 μΙ 2 U/μΙ Phusion Green Hot Start II High-Fidelity DNA polymerase (Thermo scientific, MA, USA), 10 μΙ 5x Green HF PCR buffer (F-537), 5 μΙ template DNA and 23,5 μΙ sterile water. The PCR reaction was run in a thermocycler (MJ Research, MA, USA) as follows: initial denaturation at 98 °C for 5 min, followed by 25 cycles with denaturation at 94 °C for 1 min, annealing for 10 sec at 50 °C and extension for 1 min at 72 °C, and then a final extension at 72 °C for 10 min. The PCR products were detected with agarose gel (1 .5 %) electrophoresis (120 V, 1 h). Quantitative PCR was done

Quantitative PCRs were carried out with the Light Cycler 96 Quantitative real-time PCR machine (MJ Research, MA, USA). The forward primer is pE 5 ^' -AAA CTC AAA 5 GGA ATT GAC GG-3 ^* (SEQ ID NO:3) and the reverse primer pF 5 ^' -ACG AGC TGA CGA CAG CCA TG-3 ^* (SEQ ID NO: 4) (Oqvist et al. 2008). All samples were run in triplicates in 20 μΙ reactions containing 10 μΙ 2x PowerUp SYBR Green Master Mix (Thermo scientific, MA, USA), 0.2 μΙ 20 mg/ml BSA, 0.5 μΙ of each primer (10 μΜ), and the sample template. A standard curve was included in every run to allow 10 quantitation of the number of bacterial 16S copies present in the original sample. The q-PCR run was as follows: initial denaturation at 95 °C for 2 min, followed by 40 cycles of denaturation at 95 °C for 10 s, annealing for 20 sec at 53 °C and extension for 30 s at 72 °C.

The PCR (not qPCR) products was sent to Institute for Molecular Medicine Finland 15 (FIMM), Helsinki Institute of Life Science (HiLIFE) at the University of Helsinki for MiSeq sequencing (lllumina). In the second PCR-step full length adapters and Indexes were introduced. The sequencing was done as paired-end (300bp+300bp) on a MiSeq lllumina instrument using a v3 reagent kit.

Raw sequencing data was processed using Mothur (version 1 .39.5, Schloss et al., 20 2009). The sequence processing protocol partly followed the pipeline suggested by Schloss, Gevers & Westcott (201 1 ) and Kozich et al. (2013). The paired sequences contained in reverse and forward fastq files were aligned into a contig. Sequences were trimmed and screened to remove any that had mismatches with primer or DNA- tag sequences, ambiguous bases or homopolymers larger than 8 bp long.

25 Bacterial sequences were aligned against a SILVA reference (Release 132 , Pruesse et al., 2007), preclustered to minimize sequencing errors (Huse et al., 2010) and screened for chimeras with VSEARCH (Rognes et al., 2016), which uses the abundant sequences as a reference. The chimeric sequences were removed and non-chimeric sequences were classified using the Mothur version of Bayesian

30 classifier (Wang et al., 2007) with the RDP training set version 16 (Cole et al., 2009) with 80% bootstrap threshold. Sequences classified to Chloroplast, Mitochondria, unknown, Archaea and Eukaryota were removed from the analyses. Sequences were clustered to OTUs at 97% similarity using nearest neighbour joining that conservatively assigns sequences to OTUs. Low abundance OTUs were removed (less than 10 sequences across all experimental units) as they may be PCR or sequencing artifacts (Tedersoo et al., 2010; Brown et al., 2015). We estimated bacterial diversity indices in mothur. Observed OTU richness (Sobs), the complement of Simpson's diversity (1/D), and Simpson's evenness (ED), were iteratively calculated after subsampling to 1978 sequences per sample. The value of this index starts with 1 as the lowest possible figure. This figure would represent a community containing only one species. The higher the value, the greater the diversity. The maximum value is the number of species (or other category being used) in the sample. For example if there are five species in the sample, then the maximum value is 5. We also used bacterial OTUs to list all potentially pathogenic genera in the bulk landscaping materials and the enhanced landscaping materials. Altogether 34 genera of all the 136 genera listed in Taylor et al. (2001 ) were found in the whole data. Samples of bulk landscaping materials included potentially pathogenic 19 genera while microbiologically diverse material had 15 genera, respectively. In comparison, six mineral soil samples (i.e. bulk landscaping materials in use) taken from normal urban playgrounds contained 23 potentially pathogenic genera. No pathogenic OTUs were found in microbiologically diverse material that was used to manufacture microbiologically rich, immunomodulatory landscaping materials. This revelation is important and novel as it shows that it is possible to exclude pathogens by selecting raw materials and processing them properly before they are used as part of landscaping materials.

Differences in bacterial richness and diversity between bulk and enhanced materials were evaluated using paired-t-tests. OTU richness and Simpson's diversity were significantly (p < 0.05) higher in skin swabs taken after using test tubes than those taken after touching bulk mineral landscaping materials. Number of 16S sequences (i.e. bacterial abundance) per fingertip skin sample was 478±179 and 219800±125913 (mean±SD) in fingers that touched bulk and enhanced materials, respectively (t = 4.01 , p < 0.01 ). This finding is surprising and important as it shows how an immunomodulatory landscaping material according to the current invention increases bacterial abundance, richness and diversity on skin. It is thus important as it shows a way to manufacture immunomodulatory landscaping materials consisting mostly of mineral soil particles, and still having the surprising ability to increase skin bacterial abundance and diversity when touched.

Different non-binding example aspects and embodiments of the present invention have been illustrated in the foregoing. The above embodiments are used merely to explain selected aspects or steps that may be utilized in implementations of the present invention. Some embodiments may be presented only with a reference to a certain aspect of the invention. It should be appreciated that the embodiments may apply to other aspects as well. Any appropriate combination of the embodiments and the aspects may be formed.

In an embodiment at least one component of the composition has a different structural or physical characteristic compared to a corresponding natural component from which the at least one component is derived from. In an embodiment the characteristic is uniform size or homogeneous dispersion in the composition. Literature

Alexeyev OA. 2013. Bacterial landscape of human skin: seeing the forest for the trees. Experimental Dermatology, 2013, 22, 443-446.

Berry D,Mahfoudh KB,WagnerM, et al. (201 1 ) Barcoded primers used in multiplex amplicon py-rosequencing bias amplification. Appl Environ Microb 77: 7846-9.

Caporaso, J. G., Lauber, C. L, Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S., M., Betley, J., Fraser, L., Bauer, M., Gormley, N., Gilbert, J. A., Smith, G. & Knight, R. (2012) Ultra-high-throughput microbial community analysis on the lllumina HiSeq and MiSeq platforms. The ISME Journal 6: 1621-1624.

Cole, J. R., Wang, Q., Cardenas, E., Fish, J., Chai, B., Farris, R. J., Kuluam- Syed_hoideen, A. S., McGarrell, D. M., Marsh, T., Garrity, G. M. &. Tiedje, J. M. (2009). The Ribosomal Database Project: Improved alignments and new tools for rRNA analysis. Nucleic Acids Research 37, D141 -D145.

Coyte KZ, Tabuteau H, Gaffney EA, Foster KR, Durham WM. 2016. Microbial competition in porous environments can select against rapid biofilm growth. Proceeding of the National Academy of Sciences Published Online 22 ^nd Dec. 2016,

E161-E170, w .pnas.orq/cQi/doi/10.1073/pnas.15252281 13

Edgar R.C., Haas B.J., Clemente J.C., Quince C. & Knight R. (201 1 ) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194-2200.

Hanski I, von Hertzen L, Fyhrquist N, Koskinen K, Torppa K, Laatikainen T, Karisola P, Auvinen P, Paulin L, Makela MJ, Vartiainen E, Kosunen TU, Alenius H, Haahtela

T. 2012. Environmental biodiversity, human microbiota and allergy are interrelated.

Proceeding of the National Academy of Sciences 109, 21 , 8334-8339.

Huse S.M., Welch D.M., Morrison H.G. & Sogin M.L. (2010) Ironing out the wrinkle in the rare bioshphere through improved OTU clustering. Environmental Microbiology 12, 1889-1898.

Jones SE, Lennon JT. 201 1 . Dormancy contributes to the maintenance of microbial diversity. Proceeding of the National Academy of Sciences 107, 13, 5881-5886 Kaiser C, Franklin O, Richter A, Dieckmann U. 2015. Social dynamics within decomposer communities lead to nitrogen retention and organic matter build-up in soils. Nature Communications 6: 8960, DOI: 10.1038/ncomms9960

Kozich J.J., Westcott S.L., Baxter NT., Highlander S.K. & Schloss P.D. (2013) Development of dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on MiSeq illumina sequencing platform. Applied and Environmental Microbiology 79, 51 12-5120.

Legendre, P. & Gallagher, E. D. (2001 ) Ecologically meaningful transformations for ordination of species data. Oecologia 129: 271-280.

Legendre P. & Legendre L. (2012) Numerical Ecology. 3rd edition. Elsevier, p. 310. Oqvist, C. et al.. 2008. Prokaryotic microbiota of recycled paper mills with low or zero effluent. J Ind Microbiol Biotechnology. 35: 1 165 - 1 173.

Pruesse, E., Quast, C, Knittel, K., Fuchs, B. M., Ludwig, W., Peplies, J., & Glockner, F. O. (2007). SILVA a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research, 35(21 ), 7188-7196. http://doi.Org/0.1093/nar/gkm864

Rao, Radhakrishna (1995) A review of canonical coordinates and an alternative to correspondence analysis using Hellinger distance. Questiio 19: 23-63.

5 Schloss, P. D., Gevers, D. & Westcott, S. L. (201 1 ) Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies. PLoS ONE, 6: e27310.

Schmidt TSB, Matias Rodrigues JF, von Mering C (2014) Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale. PLoS Comput Biol 10 10(4): e1003594. doi:10.1371/journal.pcbi.1003594

UNFCCC (2002), Report of the Conference of the Parties on its Seventh Session, Held at Marrakesh from 29 October to 10 November 2001 , UNFCCC, Rio de Janeiro, FCCC/CP/2001/13, United Nations

Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid 15 assignment of rRNA sequences into the new bacterial taxonomy. AppI Environ Microbiol 73: 5261-5267.

Veach, A., Dodds, W. & Jumpponen, A. (2015) Woody plant encroachment, and its removal, impact bacterial and fungal communities across stream and terrestrial habitats in a tallgrass prairie ecosystem. FEMS Microbiology Ecology 91 :1 -1 1 .

20 Wust RAJ, Bustin RM, Lavkulich LM 2003. New classification systems for tropical organic-rich deposits based on studies of the Tasek Bera Basin, Malaysia. Catena 53, 2003, 133-163

Edwards U, Rogall T, Blocker H, et al. 1989: Isolation and direct complete nucleotide determination of entire genes. Characterization of a gene coding for 16S ribosomal 25 RNA. - Nucleic Acids Res 17:7843-53. On 14.1 1 .2016 15:51 .

Koskinen, K., Hultman, J., Paulin, L., Auvinen., P. & Kankaanpaa, H. 201 1 : Spatially differing bacterial communities in water columns of the northern Baltic Sea. - FEMS Microbiol Ecol. 75(1 ):99-1 10. doi: 10.1 1 1 1/j.1574-6941 .2010.00987.x. Epub 2010 Nov 9.

30 Rognes T, Flouri T, Nichols B, et al. VSEARCH: a versatile open source tool for metagenomics[J]. PeerJ, 2016, 4: e2584. Tedersoo, L, Nilsson, R.H., Abarenkov, K., Jairus, T., Sadam, A., Saar, I., et al. (2010) 454 Pyrosequencing and Sanger sequencing of tropical mycorrhizal fungi provide similar results but reveal substantial methodological biases. New Phytol 188: 291-301 .

Brown, S.P., Veach, A.M., Rigdon-Huss, A.R., Grond, K., Lickteig, S.K., Lothamer, K., et al. (2015) Scraping the bottom of the barrel: Are rare high throughput sequences artifacts? Fungal Ecol 13: 221-225.

Oqvist, C. et al.. 2008. Prokaryotic microbiota of recycled paper mills with low or zero effluent. J Ind Microbiol Biotechnology. 35: 1 165 - 1 173.

Taylor LH, Latham SM, Woolhouse MEJ (2001 ) Risk factors for human disease emergence. Phil. Trans. R. Soc. Lond. B 356, 983-989.

Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. 2009. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75:7537-7541 .

Simpson EH. 1949. Measurement of diversity. Nature 163: 688.