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.

Abstract 870: Immunoscore® workflow enhanced by artificial intelligence

Artificial Intelligence (AI) along with Machine Learning (ML) techniques has long promised to accelerate Digital Pathology (DP) based cancer diagnosis. Despite the consensus regarding the value of AI, the lack of visibility of how ML algorithms work, prevents their wider adoption for human in vitro diagnostic (IVD) in a highly regulated environment. A common ground becomes necessary in order to fully benefit from ML capabilities.

HalioDx Immunoscore® was the first immune scoring test validated for IVD use leveraging advanced image analysis. In brief, for each tumor sample, 2 slides are stained using an automated immunohistochemistry instrument: one with CD3 and one with CD8 ready-to-use monoclonal antibodies (HalioDx) followed by detection with DAB and counterstaining. Digital images of stained slides are obtained using a whole slide scanner and analyzed by a software program (Immunoscore® Analyzer, HalioDx)1.

Current workflow relies only on Computer Vision (CV) techniques for image analysis leading to the calculation of the Immunoscore®. We have used ML to improve HalioDx Immunoscore® software program, streamline the workflow, decrease hands-on and computation times.

In summary, to design the new workflow, each DP steps were considered as independent applications. CV remains applied to the cell detection. A Convolutional Neural Network, along with a UNET architecture, were used to recognize Regions of Interest (ROI) and image-related artifacts during the analysis. Intermediary validation steps by a trained operator were maintained in order to review CV and AI steps and guarantee a complete equivalence versus the standardized original DP protocol.

The Intersection over the Union of two regions (IoU) was used as performance and equivalency metric. Compared to Ground Truth, the ML algorithm improves the accuracy of the ROI detection versus the CV based algorithm, resulting in a dramatic decrease of the ROI computing time (from 3h to 5min) as well as in a reduced need for manual correction.

We demonstrated that ML applied to the Immunoscore® DP workflow for ROI detection results in reduced time-to result and overall improved robustness of the analysis. The equivalency study showed the importance of a well-curated dataset to maximize model's accuracy and performance. Finally, the verification and validation phase demonstrated the ML based workflow readiness for regulatory approval.

1Hermitte F. J Immunother Cancer. 2016 Sep 20;4:57. doi: 10.1186/s40425-016-0161-x.

Citation Format: Assil Benchaaben, Felipe Machado Guimaraes, Emmanuel Prestat, Alboukadel Kassambara, Mounia Filahi, Caroline Laugé, Thomas Sbarrato, Jacques Fieschi. Immunoscore® workflow enhanced by artificial intelligence [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 870.

Abstract 2796: Validation of Brightplex, a multiplexed IHC solution for immune cell phenotyping of the tumor microenvironment

Brightplex is a multiplexing solution developed by HalioDx to analyze the tumor microenvironment on FFPE tissue. It leverages chromogenic immunohistochemistry performed by iterative automated immunostaining on the same slide followed by whole slide digital pathology analysis based on proprietary software combined to Halo from Indica Lab. Stained cells can be quantified in various regions of interest (tumor, stroma, invasion margin). The Brightplex T cell exhaustion (TCE) panel includes 5 biomarkers (CD3, CD8, PD1, TIM3 and LAG3) to assess the expression of three immune checkpoints on T cells. This panel is intended to be used in clinical research to identify patients susceptible to respond to new immunotherapies especially in the context of the resistance to anti PD(L)1 treatment. Therefore, it is critical to thoroughly demonstrate the robustness and the accuracy of such complex assay. For the validation study of the TCE panel, tissue sections were sequentially immunostained for TIM3, PD1, LAG3, CD8 and CD3. Following each immunostaining, the slides were digitized, de-stained and the antibodies stripped before the next immunostaining. Images of the whole slide were then coregistered and analyzed by digital pathology to determine the densities of various T cell populations: CD8+ T lymphocytes expressing of 1, 2 or 3 immune checkpoints. The precision of the assay was evaluated in terms of intra- and inter-run repeatability and the accuracy was evaluated by comparison of the automated multiplex assay with singleplex staining. Results demonstrate the reliability of Brightplex to analyze tumor sections. The precision study showed that Brightplex was reproductible on several tumor types such as NSCLC, colon and breast and the accuracy was demonstrated by comparison of cell density for each biomarker following either multiplex or singleplex staining. The high degree of robustness could be explained notably by the iterative chromogenic immunohistochemistry technology which limits the risks of steric hindrance when antibodies and amplification systems are used simultaneously and by the intrinsic robustness of this routine workflow including IVD grade instrument and reagents.

Citation Format: Aurélie Collignon, Assil Benchaaben, Alboukadel Kassambara, Felipe Guimaraes, Emmanuel Prestat, Christophe Haond, Jacques Fieschi. Validation of Brightplex, a multiplexed IHC solution for immune cell phenotyping of the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2796.

Abstract A182: T-cell exhaustion assessment using a fully automated sequential chromogenic multiplex assay

Cancer immunotherapy by anti-PD-1 or anti-PD-L1 antibodies is now established as an efficient approach to restore the cytotoxic activity of exhausted T-cells. However, the strong and durable response observed in non-small cell lung cancer (NSCLC) patients is limited to a fraction of the treated population. Biomarkers, such as PD-L1 expression on tumor cells or tumor mutational burden, are approved as predictive markers of the response to anti-PD-1 or anti-PD-L1 antibodies. However, they are far from perfect to select patients eligible to immunotherapy. Since exhausted T-cells express more than one checkpoint inhibitor, it is hypothesized that an anti-PD1 antibody may not be sufficient to restore the activity of exhausted cells. Multiplex detection of the major immune checkpoints, i.e., PD-1, LAG-3 and TIM-3, on T-cells within the tumor microenvironment could, on one hand, predict the poor response to a single agent and could, on the other hand, predict the best combination of antibodies targeting more than one immune checkpoint. Here we present an automated sequential chromogenic multiplex assay allowing the assessment of the expression of PD-1, LAG-3 and TIM-3 on CD3+/CD8+ cells on a single FFPE tumor tissue section. Briefly, a tissue section is sequentially stained, digitized, unstained and restained with antibodies targeting the five markers. Images of the whole slide are then analyzed by digital pathology. First, a newly developed software is used to co-register the 5 virtual slides and perform colors deconvolution. Detection of positive cells is performed for each marker independently, using Indica Lab’s HALO software. Then, individual cells can be analyzed to identify complex phenotypes and assess their density on the entire tissue section. In addition, tissue segmentation tools are used to assess densities of exhausted T-cells expressing the major immune checkpoints in parenchyma, tumor stroma and invasive margin regions. The quantitative evaluation of T-cells’ exhaustion based on the expression of more than one immune checkpoint could improve patient stratification and lead to individualized combinations of immunotherapy agents.

Citation Format: Aurélie Collignon, Assil Benchaaben, Anna Martirosyan, Matthieu Duval, Emilie Bonzom, Emmanuel Prestat, Christophe Haond, Jacques Fieschi. T-cell exhaustion assessment using a fully automated sequential chromogenic multiplex assay [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr A182.

Abstract 590: A new standardized CD8 and PD-L1 dual assay

PD1/PD-L1 pathway blockade results in a durable clinical response in a fraction of the non-small cell lung cancer (NSCLC) patients. Today, the expression of PD-L1, detected by immunohistochemistry (IHC) at the surface of tumor or tumor-infiltrating immune cells, is used to select patients that may respond to immune checkpoint inhibitors (ICI). However the predictive value of that biomarker alone is questioned. In order to better stratify NSCLC patients, we have developed a new dual-staining IHC assay of PD-L1+ and CD8+ cells (TILs) present in the tumor microenvironment on a single slide prepared from FFPE tissue.

The assay was optimized and fully automated on the Benchmark XT platform (Roche Ventana) with anti-PD-L1 (HDX3) and anti-CD8 (HDX2) monoclonal primary antibodies, respectively revealed with DAB and fast red substrates. Stained slides are analyzed by a pathologist like any other existing IVD test together with the TILs information. In addition, after digitization, the samples are analyzed to quantify brown and red cells with a newly developed digital Pathology (DP) tool.

The following parameters are reported by the DP tool: (1) CD8+ cell density (cells/mm²) ; (2) PD-L1+ cell density (cells/mm²) ; proximity between CD8+ and PD-L1+ cells, either centered on CD8+ or on PD-L1+ cells and finally cluster indexes for CD8+ cells and PD-L1+ cells. HalioDx DP analysis tool can calculate these parameters on any Regions Of Interest (ROI) defined by the user.

Accuracy of the automated numeration of CD8+ and PD-L1+ cells was validated by an expert pathologist. Cell-to-cell distances were validated with an independent DP tool. Variability was assessed for all parameters using adjacent dual-stained slides on complete tissue sections. The concordance with main IVD approved PD-L1 methods was established on a representative set of 55 NSCLC tumours.

HalioDx has developed an innovative assay based on the dual staining of CD8+ and PD-L1+ cells associated to a DP tool to standardize the evaluation of the tumor microenvironment. This assay could have higher predictive performance than existing IVD tests used to identify ICI resistant NSCLC patients.

Citation Format: Florence Monville, Emmanuel Prestat, Nadia Yessaad, Marine Villard, Luciana Batista, Jerome Galon, Julien Adam, Jacques Fieschi. A new standardized CD8 and PD-L1 dual assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 590. doi:10.1158/1538-7445.AM2017-590

Van der Waals pressure and its effect on trapped interlayer molecules

Van der Waals assembly of two-dimensional crystals continue attract intense interest due to the prospect of designing novel materials with on-demand properties. One of the unique features of this technology is the possibility of trapping molecules between two-dimensional crystals. The trapped molecules are predicted to experience pressures as high as 1 GPa. Here we report measurements of this interfacial pressure by capturing pressure-sensitive molecules and studying their structural and conformational changes. Pressures of 1.2±0.3 GPa are found using Raman spectrometry for molecular layers of 1-nm in thickness. We further show that this pressure can induce chemical reactions, and several trapped salts are found to react with water at room temperature, leading to two-dimensional crystals of the corresponding oxides. This pressure and its effect should be taken into account in studies of van der Waals heterostructures and can also be exploited to modify materials confined at the atomic interfaces.

Quality Heterostructures from Two-Dimensional Crystals Unstable in Air by Their Assembly in Inert Atmosphere

Many layered materials can be cleaved down to individual atomic planes, similar to graphene, but only a small minority of them are stable under ambient conditions. The rest react and decompose in air, which has severely hindered their investigation and potential applications. Here we introduce a remedial approach based on cleavage, transfer, alignment, and encapsulation of air-sensitive crystals, all inside a controlled inert atmosphere. To illustrate the technology, we choose two archetypal two-dimensional crystals that are of intense scientific interest but are unstable in air: black phosphorus and niobium diselenide. Our field-effect devices made from their monolayers are conductive and fully stable under ambient conditions, which is in contrast to the counterparts processed in air. NbSe2 remains superconducting down to the monolayer thickness. Starting with a trilayer, phosphorene devices reach sufficiently high mobilities to exhibit Landau quantization. The approach offers a venue to significantly expand the range of experimentally accessible two-dimensional crystals and their heterostructures.

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.

Real-time imaging and elemental mapping of AgAu nanoparticle transformations

We report the controlled alloying, oxidation, and subsequent reduction of individual AgAu nanoparticles in the scanning transmission electron microscope (STEM). Through sequential application of electron beam induced oxidation and in situ heating and quenching, we demonstrate the transformation of Ag-Au core-shell nanoparticles into: AgAu alloyed, Au-Ag core-shell, hollow Au-Ag2O core-shell, and Au-Ag2O yolk-shell nanoparticles. We are able to directly image these morphological transformations in real-time at atomic resolution and perform energy dispersive X-ray (EDX) spectrum imaging to map changing elemental distributions with sub-nanometre resolution. By combining aberration corrected STEM imaging and high efficiency EDX spectroscopy we are able to quantify not only the growth and coalescence of Kirkendall voids during oxidation but also the compositional changes occurring during this reaction. This is the first time that it has been possible to track the changing distribution of elements in an individual nanoparticle undergoing oxidation driven shell growth and hollowing.

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/.

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.

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.

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.

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.

Crossover from spin accumulation into interface states to spin injection in the germanium conduction band

Electrical spin injection into semiconductors paves the way for exploring new phenomena in the area of spin physics and new generations of spintronic devices. However the exact role of interface states in the spin injection mechanism from a magnetic tunnel junction into a semiconductor is still under debate. In this Letter, we demonstrate a clear transition from spin accumulation into interface states to spin injection in the conduction band of n-Ge. We observe spin signal amplification at low temperature due to spin accumulation into interface states followed by a clear transition towards spin injection in the conduction band from 200 K up to room temperature. In this regime, the spin signal is reduced to a value compatible with the spin diffusion model. More interestingly, the observation in this regime of inverse spin Hall effect in germanium generated by spin pumping and the modulation of the spin signal by a gate voltage clearly demonstrate spin accumulation in the germanium conduction band.

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.