Pooled allogeneic faecal microbiota MaaT013 for steroid-resistant gastrointestinal acute graft-versus-host disease: a single-arm, multicentre phase 2 trial.

Background: Failure of gastrointestinal acute graft-versus-host disease (GI-aGvHD) to respond to steroid therapy is associated with limited further therapeutic options. We aimed to assess the safety and efficacy of the first-in-human use of the pooled allogeneic faecal microbiota, MaaT013, for the treatment of steroid-refractory GI-aGvHD. Methods: This prospective, international, single-arm, phase 2a study reports clinical outcomes from a 24-patient cohort with grade III-IV, steroid refractory GI-aGvHD treated with the pooled allogeneic faecal microbiota MaaT013. MaaT013 involved pooling faecal matter from 3 to 8 screened donors then transplanting the pooled batches into patients to treat GI-aGVHD. The 24 patients were treated in the HERACLES study (Aug 2018 to Nov 2020) at 26 sites in Europe and an additional 52 patients were treated in a compassionate use/expanded access program (EAP) in France (July 2018 to April 2021). The primary endpoint was GI response at day 28, defined as the proportion of patients with GI-aGvHD who had a complete response (CR) or very good partial response (VGPR). GvHD grading and staging were assessed according to the revised Glucksberg criteria. Adverse events and severe adverse events were monitored for 6 months and 12 months, respectively. The HERACLES study was registered with ClinicalTrials.gov (NCT03359980). Findings: Compared with single donors, MaaT013 is characterised by higher microbial richness and reduced variability across batches. At day 28 (D28), the GI-overall response rate (ORR) was 38% in the prospective population, including 5 complete responses (CR), 2 very good partial responses (VGPR) and 2 partial responses (PR). In the EAP, the GI-ORR was 58% (17 CR, 9 VGPR and 4 PR). The 12-month overall survival (OS) was 25% in the prospective study and 38% in the EAP. Regarding safety, five infectious complications, including 3 sepsis, could not be excluded from being related to the study procedure in HERACLES. Shotgun sequencing analyses of the identified strains suggest that none were found in MaaT013. In the EAP, 18 pharmacovigilance cases were reported among 52 treated patients, including 11 bacteraemia/sepsis. In HERACLES, we observed in stools from responding patients at D28 a higher microbiota richness and increased levels of beneficial bacteria, in particular butyrate producers, along with increased levels of short-chain fatty acid and bile acids. In contrast, stools from non-responding (NR) patients displayed increased levels of pathogenic pro-inflammatory bacteria along with increased systemic inflammatory parameters. Interpretation: Overall, MaaT013 was safe in this population of highly immunocompromised patients and was associated with responses in some patients with GI-aGvHD and deserves further investigation. Funding: MaaT Pharma.

A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog.

The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering co-abundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species.

Landscape topography structures the soil microbiome in arctic polygonal tundra.

In the Arctic, environmental factors governing microbial degradation of soil carbon (C) in active layer and permafrost are poorly understood. Here we determined the functional potential of soil microbiomes horizontally and vertically across a cryoperturbed polygonal landscape in Alaska. With comparative metagenomics, genome binning of novel microbes, and gas flux measurements we show that microbial greenhouse gas (GHG) production is strongly correlated to landscape topography. Active layer and permafrost harbor contrasting microbiomes, with increasing amounts of Actinobacteria correlating with decreasing soil C in permafrost. While microbial functions such as fermentation and methanogenesis were dominant in wetter polygons, in drier polygons genes for C mineralization and CH4 oxidation were abundant. The active layer microbiome was poised to assimilate N and not to release N2O, reflecting low N2O flux measurements. These results provide mechanistic links of microbial metabolism to GHG fluxes that are needed for the refinement of model predictions.

Metagenomic and Metatranscriptomic Analyses Reveal the Structure and Dynamics of a Dechlorinating Community Containing Dehalococcoides mccartyi and Corrinoid-Providing Microorganisms under Cobalamin-Limited Conditions.

The aim of this study is to obtain a systems-level understanding of the interactions between Dehalococcoides and corrinoid-supplying microorganisms by analyzing community structures and functional compositions, activities, and dynamics in trichloroethene (TCE)-dechlorinating enrichments. Metagenomes and metatranscriptomes of the dechlorinating enrichments with and without exogenous cobalamin were compared. Seven putative draft genomes were binned from the metagenomes. At an early stage (2 days), more transcripts of genes in the Veillonellaceae bin-genome were detected in the metatranscriptome of the enrichment without exogenous cobalamin than in the one with the addition of cobalamin. Among these genes, sporulation-related genes exhibited the highest differential expression when cobalamin was not added, suggesting a possible release route of corrinoids from corrinoid producers. Other differentially expressed genes include those involved in energy conservation and nutrient transport (including cobalt transport). The most highly expressed corrinoid de novo biosynthesis pathway was also assigned to the Veillonellaceae bin-genome. Targeted quantitative PCR (qPCR) analyses confirmed higher transcript abundances of those corrinoid biosynthesis genes in the enrichment without exogenous cobalamin than in the enrichment with cobalamin. Furthermore, the corrinoid salvaging and modification pathway of Dehalococcoides was upregulated in response to the cobalamin stress. This study provides important insights into the microbial interactions and roles played by members of dechlorinating communities under cobalamin-limited conditions.IMPORTANCE The key chloroethene-dechlorinating bacterium Dehalococcoides mccartyi is a cobalamin auxotroph, thus acquiring corrinoids from other community members. Therefore, it is important to investigate the microbe-microbe interactions between Dehalococcoides and the corrinoid-providing microorganisms in a community. This study provides systems-level information, i.e., taxonomic and functional compositions and dynamics of the supportive microorganisms in dechlorinating communities under different cobalamin conditions. The findings shed light on the important roles of Veillonellaceae species in the communities compared to other coexisting community members in producing and providing corrinoids for Dehalococcoides species under cobalamin-limited conditions.

Insights into the respiratory tract microbiota of patients with cystic fibrosis during early Pseudomonas aeruginosa colonization.

Pseudomonas aeruginosa plays a major role in cystic fibrosis (CF) progression. Therefore, it is important to understand the initial steps of P. aeruginosa infection. The structure and dynamics of CF respiratory tract microbial communities during the early stages of P. aeruginosa colonization were characterized by pyrosequencing and cloning-sequencing. The respiratory microbiota showed high diversity, related to the young age of the CF cohort (mean age 10 years). Wide inter- and intra-individual variations were revealed. A common core microbiota of 5 phyla and 13 predominant genera was found, the majority of which were obligate anaerobes. A few genera were significantly more prevalent in patients never infected by P. aeruginosa. Persistence of an anaerobic core microbiota regardless of P. aeruginosa status suggests a major role of certain anaerobes in the pathophysiology of lung infections in CF. Some genera may be potential biomarkers of pulmonary infection state.

Reconstructing rare soil microbial genomes using in situ enrichments and metagenomics.

Despite extensive direct sequencing efforts and advanced analytical tools, reconstructing microbial genomes from soil using metagenomics have been challenging due to the tremendous diversity and relatively uniform distribution of genomes found in this system. Here we used enrichment techniques in an attempt to decrease the complexity of a soil microbiome prior to sequencing by submitting it to a range of physical and chemical stresses in 23 separate microcosms for 4 months. The metagenomic analysis of these microcosms at the end of the treatment yielded 540 Mb of assembly using standard de novo assembly techniques (a total of 559,555 genes and 29,176 functions), from which we could recover novel bacterial genomes, plasmids and phages. The recovered genomes belonged to Leifsonia (n = 2), Rhodanobacter (n = 5), Acidobacteria (n = 2), Sporolactobacillus (n = 2, novel nitrogen fixing taxon), Ktedonobacter (n = 1, second representative of the family Ktedonobacteraceae), Streptomyces (n = 3, novel polyketide synthase modules), and Burkholderia (n = 2, includes mega-plasmids conferring mercury resistance). Assembled genomes averaged to 5.9 Mb, with relative abundances ranging from rare (<0.0001%) to relatively abundant (>0.01%) in the original soil microbiome. Furthermore, we detected them in samples collected from geographically distant locations, particularly more in temperate soils compared to samples originating from high-latitude soils and deserts. To the best of our knowledge, this study is the first successful attempt to assemble multiple bacterial genomes directly from a soil sample. Our findings demonstrate that developing pertinent enrichment conditions can stimulate environmental genomic discoveries that would have been impossible to achieve with canonical approaches that focus solely upon post-sequencing data treatment.

Microbial ecology of chlorinated solvent biodegradation.

This study focused on the microbial ecology of tetrachloroethene (PCE) degradation to trichloroethene, cis-1,2-dichloroethene and vinyl chloride to evaluate the relationship between the microbial community and the potential accumulation or degradation of these toxic metabolites. Multiple soil microcosms supplied with different organic substrates were artificially contaminated with PCE. A thymidine analogue, bromodeoxyuridine (BrdU), was added to the microcosms and incorporated into the DNA of actively replicating cells. We compared the total and active bacterial communities during the 50-day incubations by using phylogenic microarrays and 454 pyrosequencing to identify microorganisms and functional genes associated with PCE degradation to ethene. By use of this integrative approach, both the key community members and the ecological functions concomitant with complete PCE degradation could be determined, including the presence and activity of microbial community members responsible for producing hydrogen and acetate, which are critical for Dehalococcoides-mediated PCE degradation. In addition, by correlation of chemical data and phylogenic microarray data, we identified several bacteria that could potentially oxidize hydrogen. These results demonstrate that PCE degradation is dependent on some microbial community members for production of appropriate metabolites, while other members of the community compete for hydrogen in soil at low redox potentials.

FOAM (Functional Ontology Assignments for Metagenomes): a Hidden Markov Model (HMM) database with environmental focus.

A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. 'profiles') were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/.

Assessment of the Deepwater Horizon oil spill impact on Gulf coast microbial communities.

One of the major environmental concerns of the Deepwater Horizon oil spill in the Gulf of Mexico was the ecological impact of the oil that reached shorelines of the Gulf Coast. Here we investigated the impact of the oil on the microbial composition in beach samples collected in June 2010 along a heavily impacted shoreline near Grand Isle, Louisiana. Successional changes in the microbial community structure due to the oil contamination were determined by deep sequencing of 16S rRNA genes. Metatranscriptomics was used to determine expression of functional genes involved in hydrocarbon degradation processes. In addition, potential hydrocarbon-degrading Bacteria were obtained in culture. The 16S data revealed that highly contaminated samples had higher abundances of Alpha- and Gammaproteobacteria sequences. Successional changes in these classes were observed over time, during which the oil was partially degraded. The metatranscriptome data revealed that PAH, n-alkane, and toluene degradation genes were expressed in the contaminated samples, with high homology to genes from Alteromonadales, Rhodobacterales, and Pseudomonales. Notably, Marinobacter (Gammaproteobacteria) had the highest representation of expressed genes in the samples. A Marinobacter isolated from this beach was shown to have potential for transformation of hydrocarbons in incubation experiments with oil obtained from the Mississippi Canyon Block 252 (MC252) well; collected during the Deepwater Horizon spill. The combined data revealed a response of the beach microbial community to oil contaminants, including prevalence of Bacteria endowed with the functional capacity to degrade oil.

Impact of fire on active layer and permafrost microbial communities and metagenomes in an upland Alaskan boreal forest.

Permafrost soils are large reservoirs of potentially labile carbon (C). Understanding the dynamics of C release from these soils requires us to account for the impact of wildfires, which are increasing in frequency as the climate changes. Boreal wildfires contribute to global emission of greenhouse gases (GHG-CO2, CH4 and N2O) and indirectly result in the thawing of near-surface permafrost. In this study, we aimed to define the impact of fire on soil microbial communities and metabolic potential for GHG fluxes in samples collected up to 1 m depth from an upland black spruce forest near Nome Creek, Alaska. We measured geochemistry, GHG fluxes, potential soil enzyme activities and microbial community structure via 16SrRNA gene and metagenome sequencing. We found that soil moisture, C content and the potential for respiration were reduced by fire, as were microbial community diversity and metabolic potential. There were shifts in dominance of several microbial community members, including a higher abundance of candidate phylum AD3 after fire. The metagenome data showed that fire had a pervasive impact on genes involved in carbohydrate metabolism, methanogenesis and the nitrogen cycle. Although fire resulted in an immediate release of CO2 from surface soils, our results suggest that the potential for emission of GHG was ultimately reduced at all soil depths over the longer term. Because of the size of the permafrost C reservoir, these results are crucial for understanding whether fire produces a positive or negative feedback loop contributing to the global C cycle.

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill.

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using (14)C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of (14)C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)'s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.

Interactions between snow chemistry, mercury inputs and microbial population dynamics in an Arctic snowpack.

We investigated the interactions between snowpack chemistry, mercury (Hg) contamination and microbial community structure and function in Arctic snow. Snowpack chemistry (inorganic and organic ions) including mercury (Hg) speciation was studied in samples collected during a two-month field study in a high Arctic site, Svalbard, Norway (79 °N). Shifts in microbial community structure were determined by using a 16S rRNA gene phylogenetic microarray. We linked snowpack and meltwater chemistry to changes in microbial community structure by using co-inertia analyses (CIA) and explored changes in community function due to Hg contamination by q-PCR quantification of Hg-resistance genes in metagenomic samples. Based on the CIA, chemical and microbial data were linked (p = 0.006) with bioavailable Hg (BioHg) and methylmercury (MeHg) contributing significantly to the ordination of samples. Mercury was shown to influence community function with increases in merA gene copy numbers at low BioHg levels. Our results show that snowpacks can be considered as dynamic habitats with microbial and chemical components responding rapidly to environmental changes.

Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours.

In this study, we discuss and apply a novel and efficient algorithm for learning a local Bayesian network model in the vicinity of the ZNF217 oncogene from breast cancer microarray data without having to decide in advance which genes have to be included in the learning process. ZNF217 is a candidate oncogene located at 20q13, a chromosomal region frequently amplified in breast and ovarian cancer, and correlated with shorter patient survival in these cancers. To properly address the difficulties in managing complex gene interactions given our limited sample, statistical significance of edge strengths was evaluated using bootstrapping and the less reliable edges were pruned to increase the network robustness. We found that 13 out of the 35 genes associated with deregulated ZNF217 expression in breast tumours have been previously associated with survival and/or prognosis in cancers. Identifying genes involved in lipid metabolism opens new fields of investigation to decipher the molecular mechanisms driven by the ZNF217 oncogene. Moreover, nine of the 13 genes have already been identified as putative ZNF217 targets by independent biological studies. We therefore suggest that the algorithms for inferring local BNs are valuable data mining tools for unraveling complex mechanisms of biological pathways from expression data. The source code is available at http://www710.univ-lyon1.fr/∼aaussem/Software.html.

Modeling of phenoxy acid herbicide mineralization and growth of microbial degraders in 15 soils monitored by quantitative real-time PCR of the functional tfdA gene.

Mineralization potentials, rates, and kinetics of the three phenoxy acid (PA) herbicides, 2,4-dichlorophenoxyacetic acid (2,4-D), 4-chloro-2-methylphenoxyacetic acid (MCPA), and 2-(4-chloro-2-methylphenoxy)propanoic acid (MCPP), were investigated and compared in 15 soils collected from five continents. The mineralization patterns were fitted by zero/linear or exponential growth forms of the three-half-order models and by logarithmic (log), first-order, or zero-order kinetic models. Prior and subsequent to the mineralization event, tfdA genes were quantified using real-time PCR to estimate the genetic potential for degrading PA in the soils. In 25 of the 45 mineralization scenarios, ∼60% mineralization was observed within 118 days. Elevated concentrations of tfdA in the range 1 × 10(5) to 5 × 10(7) gene copies g(-1) of soil were observed in soils where mineralization could be described by using growth-linked kinetic models. A clear trend was observed that the mineralization rates of the three PAs occurred in the order 2,4-D > MCPA > MCPP, and a correlation was observed between rapid mineralization and soils exposed to PA previously. Finally, for 2,4-D mineralization, all seven mineralization patterns which were best fitted by the exponential model yielded a higher tfdA gene potential after mineralization had occurred than the three mineralization patterns best fitted by the Lin model.

Structure, fluctuation and magnitude of a natural grassland soil metagenome.

The soil ecosystem is critical for human health, affecting aspects of the environment from key agricultural and edaphic parameters to critical influence on climate change. Soil has more unknown biodiversity than any other ecosystem. We have applied diverse DNA extraction methods coupled with high throughput pyrosequencing to explore 4.88 × 10(9) bp of metagenomic sequence data from the longest continually studied soil environment (Park Grass experiment at Rothamsted Research in the UK). Results emphasize important DNA extraction biases and unexpectedly low seasonal and vertical soil metagenomic functional class variations. Clustering-based subsystems and carbohydrate metabolism had the largest quantity of annotated reads assigned although <50% of reads were assigned at an E value cutoff of 10(-5). In addition, with the more detailed subsystems, cAMP signaling in bacteria (3.24±0.27% of the annotated reads) and the Ton and Tol transport systems (1.69±0.11%) were relatively highly represented. The most highly represented genome from the database was that for a Bradyrhizobium species. The metagenomic variance created by integrating natural and methodological fluctuations represents a global picture of the Rothamsted soil metagenome that can be used for specific questions and future inter-environmental metagenomic comparisons. However, only 1% of annotated sequences correspond to already sequenced genomes at 96% similarity and E values of <10(-5), thus, considerable genomic reconstructions efforts still have to be performed.

Soil-specific limitations for access and analysis of soil microbial communities by metagenomics.

Metagenomics approaches represent an important way to acquire information on the microbial communities present in complex environments like soil. However, to what extent do these approaches provide us with a true picture of soil microbial diversity? Soil is a challenging environment to work with. Its physicochemical properties affect microbial distributions inside the soil matrix, metagenome extraction and its subsequent analyses. To better understand the bias inherent to soil metagenome 'processing', we focus on soil physicochemical properties and their effects on the perceived bacterial distribution. In the light of this information, each step of soil metagenome processing is then discussed, with an emphasis on strategies for optimal soil sampling. Then, the interaction of cells and DNA with the soil matrix and the consequences for microbial DNA extraction are examined. Soil DNA extraction methods are compared and the veracity of the microbial profiles obtained is discussed. Finally, soil metagenomic sequence analysis and exploitation methods are reviewed.

Metagenomic mining for microbiologists.

Microbial ecologists can now start digging into the accumulating mountains of metagenomic data to uncover the occurrence of functional genes and their correlations to microbial community members. Limitations and biases in DNA extraction and sequencing technologies impact sequence distributions, and therefore, have to be considered. However, when comparing metagenomes from widely differing environments, these fluctuations have a relatively minor role in microbial community discrimination. As a consequence, any functional gene or species distribution pattern can be compared among metagenomes originating from various environments and projects. In particular, global comparisons would help to define ecosystem specificities, such as involvement and response to climate change (for example, carbon and nitrogen cycle), human health risks (eg, presence of pathogen species, toxin genes and viruses) and biodegradation capacities. Although not all scientists have easy access to high-throughput sequencing technologies, they do have access to the sequences that have been deposited in databases, and therefore, can begin to intensively mine these metagenomic data to generate hypotheses that can be validated experimentally. Information about metabolic functions and microbial species compositions can already be compared among metagenomes from different ecosystems. These comparisons add to our understanding about microbial adaptation and the role of specific microbes in different ecosystems. Concurrent with the rapid growth of sequencing technologies, we have entered a new age of microbial ecology, which will enable researchers to experimentally confirm putative relationships between microbial functions and community structures.