Forecasting the dynamics of a complex microbial community using integrated meta-omics.

Predicting the behaviour of complex microbial communities is challenging. However, this is essential for complex biotechnological processes such as those in biological wastewater treatment plants (BWWTPs), which require sustainable operation. Here we summarize 14 months of longitudinal meta-omics data from a BWWTP anaerobic tank into 17 temporal signals, explaining 91.1% of the temporal variance, and link those signals to ecological events within the community. We forecast the signals over the subsequent five years and use 21 extra samples collected at defined time intervals for testing and validation. Our forecasts are correct for six signals and hint on phenomena such as predation cycles. Using all the 17 forecasts and the environmental variables, we predict gene abundance and expression, with a coefficient of determination ≥0.87 for the subsequent three years. Our study demonstrates the ability to forecast the dynamics of open microbial ecosystems using interactions between community cycles and environmental parameters.

Water table fluctuations affect dichloromethane biodegradation in lab-scale aquifers contaminated with organohalides.

Dichloromethane (DCM) is a toxic industrial solvent frequently detected in multi-contaminated aquifers. It can be degraded biotically or abiotically, and under oxic or anoxic conditions. The extent and pathways of DCM degradation in aquifers may thus depend on water table fluctuations and microbial responses to hydrochemical variations. Here, we examined the effect of water table fluctuations on DCM biodegradation in two laboratory aquifers fed with O2-depleted DCM-spiked groundwater from a well-characterized former industrial site. Hydrochemistry, stable isotopes of DCM (δ13C and δ37Cl), and bacterial community composition were examined to determine DCM mass removal and degradation pathways under steady-state (static water table) and transient (fluctuating water table) conditions. DCM mass removal was more pronounced under transient (95%) than under steady-state conditions (42%). C and Cl isotopic fractionation values were larger under steady-state (εbulkC = -23.6 ± 3.2‰, and εbulkCl= -8.7 ± 1.6‰) than under transient conditions (εbulkC = -11.8 ± 2.0‰, and εbulkCl = -3.1 ± 0.6‰). Dual C-Cl isotope analysis suggested the prevalence of distinct anaerobic DCM degradation pathways, with ΛC/Cl values of 1.92 ± 0.30 and 3.58 ± 0.42 under steady-state and transient conditions, respectively. Water table fluctuations caused changes in redox conditions and oxygen levels, resulting in a higher relative abundance of Desulfosporosinus (Peptococcaceae family). Taken together, our results show that water table fluctuations enhanced DCM biodegradation, and correlated with bacterial taxa associated with anaerobic DCM degradation. Our integrative approach allows to evaluate anaerobic DCM degradation under dynamic hydrogeological conditions, and may help improving bioremediation strategies at DCM contaminated sites.

Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies.

In recent years, multi-omic studies have enabled resolving community structure and interrogating community function of microbial communities. Simultaneous generation of metagenomic, metatranscriptomic, metaproteomic, and (meta) metabolomic data is more feasible than ever before, thus enabling in-depth assessment of community structure, function, and phenotype, thus resulting in a multitude of multi-omic microbiome datasets and the development of innovative methods to integrate and interrogate those multi-omic datasets. Specifically, the application of reference-independent approaches provides opportunities in identifying novel organisms and functions. At present, most of these large-scale multi-omic datasets stem from spatial sampling (e.g., water/soil microbiomes at several depths, microbiomes in/on different parts of the human anatomy) or case-control studies (e.g., cohorts of human microbiomes). We believe that longitudinal multi-omic microbiome datasets are the logical next step in microbiome studies due to their characteristic advantages in providing a better understanding of community dynamics, including: observation of trends, inference of causality, and ultimately, prediction of community behavior. Furthermore, the acquisition of complementary host-derived omics, environmental measurements, and suitable metadata will further enhance the aforementioned advantages of longitudinal data, which will serve as the basis to resolve drivers of community structure and function to understand the biotic and abiotic factors governing communities and specific populations. Carefully setup future experiments hold great potential to further unveil ecological mechanisms to evolution, microbe-microbe interactions, or microbe-host interactions. In this article, we discuss the challenges, emerging strategies, and best-practices applicable to longitudinal microbiome studies ranging from sampling, biomolecular extraction, systematic multi-omic measurements, reference-independent data integration, modeling, and validation.

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE-host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR-Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid-host and phage-host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant 'Candidatus Microthrix parvicella' population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

Dichloromethane Degradation Pathway from Unsequenced Hyphomicrobium sp. MC8b Rapidly Explored by Pan-Proteomics.

Several bacteria are able to degrade the major industrial solvent dichloromethane (DCM) by using the conserved dehalogenase DcmA, the only system for DCM degradation characterised at the sequence level so far. Using differential proteomics, we rapidly identified key determinants of DCM degradation for Hyphomicrobium sp. MC8b, an unsequenced facultative methylotrophic DCM-degrading strain. For this, we designed a pan-proteomics database comprising the annotated genome sequences of 13 distinct Hyphomicrobium strains. Compared to growth with methanol, growth with DCM induces drastic changes in the proteome of strain MC8b. Dichloromethane dehalogenase DcmA was detected by differential pan-proteomics, but only with poor sequence coverage, suggesting atypical characteristics of the DCM dehalogenation system in this strain. More peptides were assigned to DcmA by error-tolerant search, warranting subsequent sequencing of the genome of strain MC8b, which revealed a highly divergent set of dcm genes in this strain. This suggests that the dcm enzymatic system is less strongly conserved than previously believed, and that substantial molecular evolution of dcm genes has occurred beyond their horizontal transfer in the bacterial domain. Our study showed the power of pan-proteomics for quick characterization of new strains belonging to branches of the Tree of Life that are densely genome-sequenced.

Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance.

The development of reliable, mixed-culture biotechnological processes hinges on understanding how microbial ecosystems respond to disturbances. Here we reveal extensive phenotypic plasticity and niche complementarity in oleaginous microbial populations from a biological wastewater treatment plant. We perform meta-omics analyses (metagenomics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekly intervals. Based on 1,364 de novo metagenome-assembled genomes, we uncover four distinct fundamental niche types. Throughout the time-series, we observe a major, transient shift in community structure, coinciding with substrate availability changes. Functional omics data reveals extensive variation in gene expression and substrate usage amongst community members. Ex situ bioreactor experiments confirm that responses occur within five hours of a pulse disturbance, demonstrating rapid adaptation by specific populations. Our results show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity, and set the foundation for future ecological engineering efforts.

Determining Microbial Niche Breadth in the Environment for Better Ecosystem Fate Predictions.

Integrated omics applied to microbial communities offers a great opportunity to analyze the niche breadths (i.e., resource and condition ranges usable by a species) of constituent populations, ranging from generalists, with a broad niche breadth, to specialists, with a narrow one. In this context, extracellular metabolomics measurements describe resource spaces available to microbial populations; dedicated analyses of metagenomics data serve to describe the fundamental niches of constituent populations, and functional meta-omics becomes a proxy to characterize the realized niches of populations and their variations though time or space. Thus, the combination of environmental omics and its thorough interpretation allows us to directly describe niche breadths of constituent populations of a microbial community, precisely and in situ This will greatly facilitate studies of the causes influencing ecosystem stability, resistance, and resilience, as well as generation of the necessary knowledge to model and predict the fate of any ecosystem in the current context of global change.

Sequential Isolation of DNA, RNA, Protein, and Metabolite Fractions from Murine Organs and Intestinal Contents for Integrated Omics of Host-Microbiota Interactions.

The gastrointestinal microbiome plays a central role in health and disease. Imbalances in the microbiome, also referred to as dysbiosis, have recently been associated with a number of human idiopathic diseases ranging from metabolic to neurodegenerative. However, to causally link specific microorganisms or dysbiotic communities with tissue-specific and/or systemic disease-associated phenotypes, systematic in vivo studies are fundamental. Gnotobiotic mouse models have proven to be particularly useful for the elucidation of microbiota-associated characteristics as they provide a means to conduct targeted perturbations followed by analyses of induced localized and systemic effects. Here, we describe a methodology in the framework of systems biology which allows the comprehensive isolation of high quality biomolecular fractions (DNA, RNA, proteins and metabolites) from limited and/or heterogeneous sample material derived from murine brain, liver, and colon tissues, as well as from intestinal contents (fecal pellets and fecal masses). The obtained biomolecular fractions are compatible with current high-throughput genomic, transcriptomic, proteomic, and metabolomic analyses. The resulting data fulfills the premise of systematic measurements and allows the detailed study of tissue-specific and/or systemic effects of host-microbiota interactions in relation to health and disease.

Expressed protein profile of a Tectomicrobium and other microbial symbionts in the marine sponge Aplysina aerophoba as evidenced by metaproteomics.

Aplysina aerophoba is an emerging model marine sponge, with a well-characterized microbial community in terms of diversity and structure. However, little is known about the expressed functional capabilities of its associated microbes. Here, we present the first metaproteomics-based study of the microbiome of A. aerophoba. We found that transport and degradation of halogenated and chloroaromatic compounds are common active processes in the sponge microbiomes. Our data further reveal that the highest number of proteins were affiliated to a sponge-associated Tectomicrobium, presumably from the family Entotheonellaceae, as well as to the well-known symbiont "Candidatus Synechococcus spongiarium", suggesting a high metabolic activity of these two microorganisms in situ. Evidence for nitric oxide (NO) conversion to nitrous oxide was consistently observed for Tectomicrobia across replicates, by production of the NorQ protein. Moreover, we found a potential energy-yielding pathway through CO oxidation by putative Chloroflexi bacteria. Finally, we observed expression of enzymes that may be involved in the transformation of chitin, glycoproteins, glycolipids and glucans into smaller molecules, consistent with glycosyl hydrolases predicted from analyses of the genomes of Poribacteria sponge symbionts. Thus, this study provides crucial links between expressed proteins and specific members of the A. aerophoba microbiome.

A year of monitoring 20 mesophilic full-scale bioreactors reveals the existence of stable but different core microbiomes in bio-waste and wastewater anaerobic digestion systems.

BACKGROUND: Anaerobic digestion (AD) is a microbe-driven process of biomass decomposition to CH4 and CO2. In addition to renewable and cost-effective energy production, AD has emerged in the European Union as an environmentally friendly model of bio-waste valorisation and nutrient recycling. Nevertheless, due to the high diversity of uncharacterised microbes, a typical AD microbiome is still considered as "dark matter". RESULTS: Using the high-throughput sequencing of small rRNA gene, and a monthly monitoring of the physicochemical parameters for 20 different mesophilic full-scale bioreactors over 1 year, we generated a detailed view of AD microbial ecology towards a better understanding of factors that influence and shape these communities. By studying the broadly distributed OTUs present in over 80% of analysed samples, we identified putatively important core bacteria and archaea to the AD process that accounted for over 70% of the whole microbial community relative abundances. AD reactors localised at the wastewater treatment plants were shown to operate with distinct core microbiomes than the agricultural and bio-waste treating biogas units. We also showed that both the core microbiomes were composed of low (with average community abundance ≤ 1%) and highly abundant microbial populations; the vast majority of which remains yet uncharacterised, e.g. abundant candidate Cloacimonetes. Using non-metric multidimensional scaling, we observed microorganisms grouping into clusters that well reflected the origin of the samples, e.g. wastewater versus agricultural and bio-waste treating biogas units. The calculated diversity patterns differed markedly between the different community clusters, mainly due to the presence of highly diverse and dynamic transient species. Core microbial communities appeared relatively stable over the monitoring period. CONCLUSIONS: In this study, we characterised microbial communities in different AD systems that were monitored over a 1-year period. Evidences were shown to support the concept of a core community driving the AD process, whereas the vast majority of dominant microorganisms remain yet to be characterised.

First draft genome sequence of a strain belonging to the Zoogloea genus and its gene expression in situ.

The Gram-negative beta-proteobacterium Zoogloea sp. LCSB751 (LMG 29444) was newly isolated from foaming activated sludge of a municipal wastewater treatment plant. Here, we describe its draft genome sequence and annotation together with a general physiological and genomic analysis, as the first sequenced representative of the Zoogloea genus. Moreover, Zoogloea sp. gene expression in its environment is described using metatranscriptomic data obtained from the same treatment plant. The presented genomic and transcriptomic information demonstrate a pronounced capacity of this genus to synthesize poly-ß-hydroxyalkanoate within wastewater.

Genome Sequence of the Dichloromethane-Degrading Bacterium Hyphomicrobium sp. Strain GJ21.

The genome sequence of Hyphomicrobium sp. strain GJ21, isolated in the Netherlands from samples of environments contaminated with halogenated pollutants and capable of using dichloromethane as its sole carbon and energy source, was determined.

Integrated meta-omic analyses of the gastrointestinal tract microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation.

In patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT), treatment-induced changes to the gastrointestinal tract (GIT) microbiome have been linked to adverse outcomes, most notably graft-versus-host disease (GvHD). However, it is presently unknown whether this relationship is causal or consequential. Here, we performed an integrated meta-omic analysis to probe deeper into the GIT microbiome changes during allo-HSCT and its accompanying treatments. We used 16S and 18S rRNA gene amplicon sequencing to resolve archaea, bacteria, and eukaryotes within the GIT microbiomes of 16 patients undergoing allo-HSCT for the treatment of hematologic malignancies. These results revealed a major shift in the GIT microbiome after allo-HSCT including a marked reduction in bacterial diversity, accompanied by only limited changes in eukaryotes and archaea. An integrated analysis of metagenomic and metatranscriptomic data was performed on samples collected from a patient before and after allo-HSCT for acute myeloid leukemia. This patient developed severe GvHD, leading to death 9 months after allo-HSCT. In addition to drastically decreased bacterial diversity, the post-treatment microbiome showed a higher overall number and higher expression levels of antibiotic resistance genes (ARGs). One specific Escherichia coli strain causing a paravertebral abscess was linked to GIT dysbiosis, suggesting loss of intestinal barrier integrity. The apparent selection for bacteria expressing ARGs suggests that prophylactic antibiotic administration may adversely affect the overall treatment outcome. We therefore assert that such analyses including information about the selection of pathogenic bacteria expressing ARGs may assist clinicians in "personalizing" regimens for individual patients to improve overall outcomes.

Colonization and Succession within the Human Gut Microbiome by Archaea, Bacteria, and Microeukaryotes during the First Year of Life.

Perturbations to the colonization process of the human gastrointestinal tract have been suggested to result in adverse health effects later in life. Although much research has been performed on bacterial colonization and succession, much less is known about the other two domains of life, archaea, and eukaryotes. Here we describe colonization and succession by bacteria, archaea and microeukaryotes during the first year of life (samples collected around days 1, 3, 5, 28, 150, and 365) within the gastrointestinal tract of infants delivered either vaginally or by cesarean section and using a combination of quantitative real-time PCR as well as 16S and 18S rRNA gene amplicon sequencing. Sequences from organisms belonging to all three domains of life were detectable in all of the collected meconium samples. The microeukaryotic community composition fluctuated strongly over time and early diversification was delayed in infants receiving formula milk. Cesarean section-delivered (CSD) infants experienced a delay in colonization and succession, which was observed for all three domains of life. Shifts in prokaryotic succession in CSD infants compared to vaginally delivered (VD) infants were apparent as early as days 3 and 5, which were characterized by increased relative abundances of the genera Streptococcus and Staphylococcus, and a decrease in relative abundance for the genera Bifidobacterium and Bacteroides. Generally, a depletion in Bacteroidetes was detected as early as day 5 postpartum in CSD infants, causing a significantly increased Firmicutes/Bacteroidetes ratio between days 5 and 150 when compared to VD infants. Although the delivery mode appeared to have the strongest influence on differences between the infants, other factors such as a younger gestational age or maternal antibiotics intake likely contributed to the observed patterns as well. Our findings complement previous observations of a delay in colonization and succession of CSD infants, which affects not only bacteria but also archaea and microeukaryotes. This further highlights the need for resolving bacterial, archaeal, and microeukaryotic dynamics in future longitudinal studies of microbial colonization and succession within the neonatal gastrointestinal tract.

Hopanoid-free Methylobacterium extorquens DM4 overproduces carotenoids and has widespread growth impairment.

Hopanoids are sterol-like membrane lipids widely used as geochemical proxies for bacteria. Currently, the physiological role of hopanoids is not well understood, and this represents one of the major limitations in interpreting the significance of their presence in ancient or contemporary sediments. Previous analyses of mutants lacking hopanoids in a range of bacteria have revealed a range of phenotypes under normal growth conditions, but with most having at least an increased sensitivity to toxins and osmotic stress. We employed hopanoid-free strains of Methylobacterium extorquens DM4, uncovering severe growth defects relative to the wild-type under many tested conditions, including normal growth conditions without additional stressors. Mutants overproduce carotenoids-the other major isoprenoid product of this strain-and show an altered fatty acid profile, pronounced flocculation in liquid media, and lower growth yields than for the wild-type strain. The flocculation phenotype can be mitigated by addition of cellulase to the medium, suggesting a link between the function of hopanoids and the secretion of cellulose in M. extorquens DM4. On solid media, colonies of the hopanoid-free mutant strain were smaller than wild-type, and were more sensitive to osmotic or pH stress, as well as to a variety of toxins. The results for M. extorquens DM4 are consistent with the hypothesis that hopanoids are important for membrane fluidity and lipid packing, but also indicate that the specific physiological processes that require hopanoids vary across bacterial lineages. Our work provides further support to emerging observations that the role of hopanoids in membrane robustness and barrier function may be important across lineages, possibly mediated through an interaction with lipid A in the outer membrane.

IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses.

Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license).

Identification, Recovery, and Refinement of Hitherto Undescribed Population-Level Genomes from the Human Gastrointestinal Tract.

Linking taxonomic identity and functional potential at the population-level is important for the study of mixed microbial communities and is greatly facilitated by the availability of microbial reference genomes. While the culture-independent recovery of population-level genomes from environmental samples using the binning of metagenomic data has expanded available reference genome catalogs, several microbial lineages remain underrepresented. Here, we present two reference-independent approaches for the identification, recovery, and refinement of hitherto undescribed population-level genomes. The first approach is aimed at genome recovery of varied taxa and involves multi-sample automated binning using CANOPY CLUSTERING complemented by visualization and human-augmented binning using VIZBIN post hoc. The second approach is particularly well-suited for the study of specific taxa and employs VIZBIN de novo. Using these approaches, we reconstructed a total of six population-level genomes of distinct and divergent representatives of the Alphaproteobacteria class, the Mollicutes class, the Clostridiales order, and the Melainabacteria class from human gastrointestinal tract-derived metagenomic data. Our results demonstrate that, while automated binning approaches provide great potential for large-scale studies of mixed microbial communities, these approaches should be complemented with informative visualizations because expert-driven inspection and refinements are critical for the recovery of high-quality population-level genomes.

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications.

Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks.

BACKGROUND: Mixed microbial communities underpin important biotechnological processes such as biological wastewater treatment (BWWT). A detailed knowledge of community structure and function relationships is essential for ultimately driving these systems towards desired outcomes, e.g., the enrichment in organisms capable of accumulating valuable resources during BWWT. METHODS: A comparative integrated omic analysis including metagenomics, metatranscriptomics and metaproteomics was carried out to elucidate functional differences between seasonally distinct oleaginous mixed microbial communities (OMMCs) sampled from an anoxic BWWT tank. A computational framework for the reconstruction of community-wide metabolic networks from multi-omic data was developed. These provide an overview of the functional capabilities by incorporating gene copy, transcript and protein abundances. To identify functional genes, which have a disproportionately important role in community function, we define a high relative gene expression and a high betweenness centrality relative to node degree as gene-centric and network topological features, respectively. RESULTS: Genes exhibiting high expression relative to gene copy abundance include genes involved in glycerolipid metabolism, particularly triacylglycerol lipase, encoded by known lipid accumulating populations, e.g., CandidatusMicrothrix parvicella. Genes with a high relative gene expression and topologically important positions in the network include genes involved in nitrogen metabolism and fatty acid biosynthesis, encoded by Nitrosomonas spp. and Rhodococcus spp. Such genes may be regarded as 'keystone genes' as they are likely to be encoded by keystone species. CONCLUSION: The linking of key functionalities to community members through integrated omics opens up exciting possibilities for devising prediction and control strategies for microbial communities in the future.