Cryptic exon detection and transcriptomic changes revealed in single-nuclei RNA sequencing of C9ORF72 patients spanning the ALS-FTD spectrum.

The C9ORF72-linked diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are characterized by the nuclear depletion and cytoplasmic accumulation of TAR DNA-binding protein 43 (TDP-43). Recent studies have shown that the loss of TDP-43 function leads to the inclusion of cryptic exons (CE) in several RNA transcript targets of TDP-43. Here, we show for the first time the detection of CEs in a single-nuclei RNA sequencing (snRNA-seq) dataset obtained from frontal and occipital cortices of C9ORF72 patients that phenotypically span the ALS-FTD disease spectrum. We assessed each cellular cluster for detection of recently described TDP-43-induced CEs. Transcripts containing CEs in the genes STMN2 and KALRN were detected in the frontal cortex of all C9ORF72 disease groups with the highest frequency in excitatory neurons in the C9ORF72-FTD group. Within the excitatory neurons, the cluster with the highest proportion of cells containing a CE had transcriptomic similarities to von Economo neurons, which are known to be vulnerable to TDP-43 pathology and selectively lost in C9ORF72-FTD. Differential gene expression and pathway analysis of CE-containing neurons revealed multiple dysregulated metabolic processes. Our findings reveal novel insights into the transcriptomic changes of neurons vulnerable to TDP-43 pathology.

Complementary Microorganisms in Highly Corrosive Biofilms from an Offshore Oil Production Facility.

Offshore oil production facilities are frequently victims of internal piping corrosion, potentially leading to human and environmental risks and significant economic losses. Microbially influenced corrosion (MIC) is believed to be an important factor in this major problem for the petroleum industry. However, knowledge of the microbial communities and metabolic processes leading to corrosion is still limited. Therefore, the microbial communities from three anaerobic biofilms recovered from the inside of a steel pipe exhibiting high corrosion rates, iron oxide deposits, and substantial amounts of sulfur, which are characteristic of MIC, were analyzed in detail. Bacterial and archaeal community structures were investigated by automated ribosomal intergenic spacer analysis, multigenic (16S rRNA and functional genes) high-throughput Illumina MiSeq sequencing, and quantitative PCR analysis. The microbial community analysis indicated that bacteria, particularly Desulfovibrio species, dominated the biofilm microbial communities. However, other bacteria, such as Pelobacter, Pseudomonas, and Geotoga, as well as various methanogenic archaea, previously detected in oil facilities were also detected. The microbial taxa and functional genes identified suggested that the biofilm communities harbored the potential for a number of different but complementary metabolic processes and that MIC in oil facilities likely involves a range of microbial metabolisms such as sulfate, iron, and elemental sulfur reduction. Furthermore, extreme corrosion leading to leakage and exposure of the biofilms to the external environment modify the microbial community structure by promoting the growth of aerobic hydrocarbon-degrading organisms.

Merging metagenomics and geochemistry reveals environmental controls on biological diversity and evolution.

BACKGROUND: The metabolic strategies employed by microbes inhabiting natural systems are, in large part, dictated by the physical and geochemical properties of the environment. This study sheds light onto the complex relationship between biology and environmental geochemistry using forty-three metagenomes collected from geochemically diverse and globally distributed natural systems. It is widely hypothesized that many uncommonly measured geochemical parameters affect community dynamics and this study leverages the development and application of multidimensional biogeochemical metrics to study correlations between geochemistry and microbial ecology. Analysis techniques such as a Markov cluster-based measure of the evolutionary distance between whole communities and a principal component analysis (PCA) of the geochemical gradients between environments allows for the determination of correlations between microbial community dynamics and environmental geochemistry and provides insight into which geochemical parameters most strongly influence microbial biodiversity. RESULTS: By progressively building from samples taken along well defined geochemical gradients to samples widely dispersed in geochemical space this study reveals strong links between the extent of taxonomic and functional diversification of resident communities and environmental geochemistry and reveals temperature and pH as the primary factors that have shaped the evolution of these communities. Moreover, the inclusion of extensive geochemical data into analyses reveals new links between geochemical parameters (e.g. oxygen and trace element availability) and the distribution and taxonomic diversification of communities at the functional level. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial taxonomic and functional composition. CONCLUSIONS: Clustering based on the frequency in which orthologous proteins occur among metagenomes facilitated accurate prediction of the ordering of community functional composition along geochemical gradients, despite a lack of geochemical input. The consistency in the results obtained from the application of Markov clustering and multivariate methods to distinct natural systems underscore their utility in predicting the functional potential of microbial communities within a natural system based on system geochemistry alone, allowing geochemical measurements to be used to predict purely biological metrics such as microbial community composition and metabolism.

Contrasting Pathways for Anaerobic Methane Oxidation in Gulf of Mexico Cold Seep Sediments.

Gulf of Mexico sediments harbor numerous hydrocarbon seeps associated with high sedimentation rates and thermal maturation of organic matter. These ecosystems host abundant and diverse microbial communities that directly or indirectly metabolize components of the emitted fluid. To investigate microbial function and activities in these ecosystems, metabolic potential (metagenomic) and gene expression (metatranscriptomic) analyses of two cold seep areas of the Gulf of Mexico were carried out. Seeps emitting biogenic methane harbored microbial communities dominated by archaeal anaerobic methane oxidizers of phylogenetic group 1 (ANME-1), whereas seeps producing fluids containing a complex mixture of thermogenic hydrocarbons were dominated by ANME-2 lineages. Metatranscriptome measurements in both communities indicated high levels of expression of genes for methane metabolism despite their distinct microbial communities and hydrocarbon composition. In contrast, the transcription level of sulfur cycle genes was quite different. In the thermogenic seep community, high levels of transcripts indicative of syntrophic anaerobic oxidation of methane (AOM) coupled to sulfate reduction were detected. This syntrophic partnership between the dominant ANME-2 and sulfate reducers potentially involves direct electron transfer through multiheme cytochromes. In the biogenic methane seep, genes from an ANME-1 lineage that are potentially involved in polysulfide reduction were highly expressed, suggesting a novel bacterium-independent anaerobic methane oxidation pathway coupled to polysulfide reduction. The observed divergence in AOM activities provides a new model for bacterium-independent AOM and emphasizes the variation that exists in AOM pathways between different ANME lineages. IMPORTANCE Cold seep sediments are complex and widespread marine ecosystems emitting large amounts of methane, a potent greenhouse gas, and other hydrocarbons. Within these sediments, microbial communities play crucial roles in production and degradation of hydrocarbons, modulating oil and gas emissions to seawater. Despite this ecological importance, our understanding of microbial functions and methane oxidation pathways in cold seep ecosystems is poor. Based on gene expression profiling of environmental seep sediment samples, the present work showed that (i) the composition of the emitted fluids shapes the microbial community in general and the anaerobic methanotroph community specifically and (ii) AOM by ANME-2 in this seep may be coupled to sulfate reduction by Deltaproteobacteria by electron transfer through multiheme cytochromes, whereas AOM by ANME-1 lineages in this seep may involve a different, bacterium-independent pathway, coupling methane oxidation to elemental sulfur/polysulfide reduction.

MetaHCR: a web-enabled metagenome data management system for hydrocarbon resources.

The ever-increasing metagenomic data necessitate appropriate cataloguing in a way that facilitates the comparison and better contextualization of the underlying investigations. To this extent, information associated with the sequencing data as well as the original sample and the environment where it was obtained from is crucial. To date, there are not any publicly available repositories able to capture environmental metadata pertaining to hydrocarbon-rich environments. As such, contextualization and comparative analysis among sequencing datasets derived from these environments is to a certain degree hindered or cannot be fully evaluated. The metagenomics data management system for hydrocarbon resources (MetaHCRs) enables the capturing of marker gene and whole metagenome sequencing data as well as over 300 contextual attributes associated with samples, organisms, environments and geological properties, among others. Moreover, MetaHCR implements the Minimum Information about any Sequence-hydrocarbon resource specification from the Genomic Standards Consortium; it integrates a user-friendly web interface and relational database model, and it enables the generation of complex custom search. MetaHCR has been tested with 36 publicly available metagenomic studies, and its modular architecture can be easily customized for other types of environmental and metagenomics studies.

Succession in the petroleum reservoir microbiome through an oil field production lifecycle.

Subsurface petroleum reservoirs are an important component of the deep biosphere where indigenous microorganisms live under extreme conditions and in isolation from the Earth's surface for millions of years. However, unlike the bulk of the deep biosphere, the petroleum reservoir deep biosphere is subject to extreme anthropogenic perturbation, with the introduction of new electron acceptors, donors and exogenous microbes during oil exploration and production. Despite the fundamental and practical significance of this perturbation, there has never been a systematic evaluation of the ecological changes that occur over the production lifetime of an active offshore petroleum production system. Analysis of the entire Halfdan oil field in the North Sea (32 producing wells in production for 1-15 years) using quantitative PCR, multigenic sequencing, comparative metagenomic and genomic bins reconstruction revealed systematic shifts in microbial community composition and metabolic potential, as well as changing ecological strategies in response to anthropogenic perturbation of the oil field ecosystem, related to length of time in production. The microbial communities were initially dominated by slow growing anaerobes such as members of the Thermotogales and Clostridiales adapted to living on hydrocarbons and complex refractory organic matter. However, as seawater and nitrate injection (used for secondary oil production) delivered oxidants, the microbial community composition progressively changed to fast growing opportunists such as members of the Deferribacteres, Delta-, Epsilon- and Gammaproteobacteria, with energetically more favorable metabolism (for example, nitrate reduction, H2S, sulfide and sulfur oxidation). This perturbation has profound consequences for understanding the microbial ecology of the system and is of considerable practical importance as it promotes detrimental processes such as reservoir souring and metal corrosion. These findings provide a new conceptual framework for understanding the petroleum reservoir biosphere and have consequences for developing strategies to manage microbiological problems in the oil industry.

Microbial and Isotopic Evidence for Methane Cycling in Hydrocarbon-Containing Groundwater from the Pennsylvania Region.

The Pennsylvania region hosts numerous oil and gas reservoirs and the presence of hydrocarbons in groundwater has been locally observed. However, these methane-containing freshwater ecosystems remain poorly explored despite their potential importance in the carbon cycle. Methane isotope analysis and analysis of low molecular weight hydrocarbon gases from 18 water wells indicated that active methane cycling may be occurring in methane-containing groundwater from the Pennsylvania region. Consistent with this observation, multigenic qPCR and gene sequencing (16S rRNA genes, mcrA, and pmoA genes) indicated abundant populations of methanogens, ANME-2d (average of 1.54 × 104mcrA gene per milliliter of water) and bacteria associated with methane oxidation (NC10, aerobic methanotrophs, methylotrophs; average of 2.52 × 103pmoA gene per milliliter of water). Methane cycling therefore likely represents an important process in these hydrocarbon-containing aquifers. The microbial taxa and functional genes identified and geochemical data suggested that (i) methane present is at least in part due to methanogens identified in situ; (ii) Potential for aerobic and anaerobic methane oxidation is important in groundwater with the presence of lineages associated with both anaerobic an aerobic methanotrophy; (iii) the dominant methane oxidation process (aerobic or anaerobic) can vary according to prevailing conditions (oxic or anoxic) in the aquifers; (iv) the methane cycle is closely associated with the nitrogen cycle in groundwater methane seeps with methane and/or methanol oxidation coupled to denitrification or nitrate and nitrite reduction.

Comparative metagenomics of hydrocarbon and methane seeps of the Gulf of Mexico.

Oil and gas percolate profusely through the sediments of the Gulf of Mexico, leading to numerous seeps at the seafloor, where complex microbial, and sometimes animal communities flourish. Sediments from three areas (two cold seeps with contrasting hydrocarbon composition and a site outside any area of active seepage) of the Gulf of Mexico were investigated and compared. Consistent with the existence of a seep microbiome, a distinct microbial community was observed in seep areas compared to sediment from outside areas of active seepage. The microbial community from sediments without any influence from hydrocarbon seepage was characterized by Planctomycetes and the metabolic potential was consistent with detrital marine snow degradation. By contrast, in seep samples with methane as the principal hydrocarbon, methane oxidation by abundant members of ANME-1 was likely the predominant process. Seep samples characterized by fluids containing both methane and complex hydrocarbons, were characterized by abundant Chloroflexi (Anaerolinaceae) and deltaproteobacterial lineages and exhibited potential for complex hydrocarbon degradation. These different metabolic capacities suggested that microorganisms in cold seeps can potentially rely on other processes beyond methane oxidation and that the hydrocarbon composition of the seep fluids may be a critical factor structuring the seafloor microbial community composition and function.

Resolving prokaryotic taxonomy without rRNA: longer oligonucleotide word lengths improve genome and metagenome taxonomic classification.

Oligonucleotide signatures, especially tetranucleotide signatures, have been used as method for homology binning by exploiting an organism's inherent biases towards the use of specific oligonucleotide words. Tetranucleotide signatures have been especially useful in environmental metagenomics samples as many of these samples contain organisms from poorly classified phyla which cannot be easily identified using traditional homology methods, including NCBI BLAST. This study examines oligonucleotide signatures across 1,424 completed genomes from across the tree of life, substantially expanding upon previous work. A comprehensive analysis of mononucleotide through nonanucleotide word lengths suggests that longer word lengths substantially improve the classification of DNA fragments across a range of sizes of relevance to high throughput sequencing. We find that, at present, heptanucleotide signatures represent an optimal balance between prediction accuracy and computational time for resolving taxonomy using both genomic and metagenomic fragments. We directly compare the ability of tetranucleotide and heptanucleotide world lengths (tetranucleotide signatures are the current standard for oligonucleotide word usage analyses) for taxonomic binning of metagenome reads. We present evidence that heptanucleotide word lengths consistently provide more taxonomic resolving power, particularly in distinguishing between closely related organisms that are often present in metagenomic samples. This implies that longer oligonucleotide word lengths should replace tetranucleotide signatures for most analyses. Finally, we show that the application of longer word lengths to metagenomic datasets leads to more accurate taxonomic binning of DNA scaffolds and have the potential to substantially improve taxonomic assignment and assembly of metagenomic data.

Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem.

We have constructed a conceptual model of biogeochemical cycles and metabolic and microbial community shifts within a hot spring ecosystem via coordinated analysis of the "Bison Pool" (BP) Environmental Genome and a complementary contextual geochemical dataset of ~75 geochemical parameters. 2,321 16S rRNA clones and 470 megabases of environmental sequence data were produced from biofilms at five sites along the outflow of BP, an alkaline hot spring in Sentinel Meadow (Lower Geyser Basin) of Yellowstone National Park. This channel acts as a >22 m gradient of decreasing temperature, increasing dissolved oxygen, and changing availability of biologically important chemical species, such as those containing nitrogen and sulfur. Microbial life at BP transitions from a 92 °C chemotrophic streamer biofilm community in the BP source pool to a 56 °C phototrophic mat community. We improved automated annotation of the BP environmental genomes using BLAST-based Markov clustering. We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. This assignment yields high genome coverage in dominant community members, facilitating reconstruction of nearly complete metabolic profiles and in-depth analysis of the relation between geochemical and metabolic changes along the outflow. We show that changes in environmental conditions and energy availability are associated with dramatic shifts in microbial communities and metabolic function. We have also identified an organism constituting a novel phylum in a metabolic "transition" community, located physically between the chemotroph- and phototroph-dominated sites. The complementary analysis of biogeochemical and environmental genomic data from BP has allowed us to build ecosystem-based conceptual models for this hot spring, reconstructing whole metabolic networks in order to illuminate community roles in shaping and responding to geochemical variability.