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The existence of a link between the gut microbiome and autism spectrum disorder (ASD) is well established in mice, but in human populations, efforts to identify microbial biomarkers have been limited due to a lack of appropriately matched controls, stratification of participants within the autism spectrum, and sample size. To overcome these limitations, we crowdsourced the recruitment of families with age-matched sibling pairs between 2 and 7 years old (within 2 years of each other), where one child had a diagnosis of ASD and the other did not. Parents collected stool samples, provided a home video of their ASD child's natural social behavior, and responded online to diet and behavioral questionnaires. 16S rRNA V4 amplicon sequencing of 117 samples (60 ASD and 57 controls) identified 21 amplicon sequence variants (ASVs) that differed significantly between the two cohorts: 11 were found to be enriched in neurotypical children (six ASVs belonging to the Lachnospiraceae family), while 10 were enriched in children with ASD (including Ruminococcaceae and Bacteroidaceae families). Summarizing the expected KEGG orthologs of each predicted genome, the taxonomic biomarkers associated with children with ASD can use amino acids as precursors for butyragenic pathways, potentially altering the availability of neurotransmitters like glutamate and gamma aminobutyric acid (GABA).IMPORTANCE Autism spectrum disorder (ASD), which now affects 1 in 54 children in the United States, is known to have comorbidity with gut disorders of a variety of types; however, the link to the microbiome remains poorly characterized. Recent work has provided compelling evidence to link the gut microbiome to the autism phenotype in mouse models, but identification of specific taxa associated with autism has suffered replicability issues in humans. This has been due in part to sample size that sufficiently covers the spectrum of phenotypes known to autism (which range from subtle to severe) and a lack of appropriately matched controls. Our original study proposes to overcome these limitations by collecting stool-associated microbiome on 60 sibling pairs of children, one with autism and one neurotypically developing, both 2 to 7 years old and no more than 2 years apart in age. We use exact sequence variant analysis and both permutation and differential abundance procedures to identify 21 taxa with significant enrichment or depletion in the autism cohort compared to their matched sibling controls. Several of these 21 biomarkers have been identified in previous smaller studies; however, some are new to autism and known to be important in gut-brain interactions and/or are associated with specific fatty acid biosynthesis pathways.

Salinity is one of the strongest environmental drivers of microbial evolution and community composition. Here we aimed to determine the impact of salt concentrations (2.5, 7.5, and 33.2%) on the microbial community structure of reclaimed saltern ponds near San Francisco, California, and to discover prospective enzymes with potential biotechnological applications. Community compositions were determined by 16S rRNA amplicon sequencing revealing both higher richness and evenness in the pond sediments compared to the water columns. Co-occurrence network analysis additionally uncovered the presence of microbial seed bank communities, potentially primed to respond to rapid changes in salinity. In addition, functional annotation of shotgun metagenomic DNA showed different capabilities if the microbial communities at different salinities for methanogenesis, amino acid metabolism, and carbohydrate-active enzymes. There was an overall shift with increasing salinity in the functional potential for starch degradation, and a decrease in degradation of cellulose and other oligosaccharides. Further, many carbohydrate-active enzymes identified have acidic isoelectric points that have potential biotechnological applications, including deconstruction of biofuel feedstocks under high ionic conditions. Metagenome-assembled genomes (MAGs) of individual halotolerant and halophilic microbes were binned revealing a variety of carbohydrate-degrading potential of individual pond inhabitants.

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/.

A metagenomic approach that combines molecular screening and pyrosequencing is used for characterizing operons encoding enzymes involved in denitrification, a nitrogen-cycling process involved in nitrogen losses and greenhouse gas emission. The screening of several clones from a soil metagenomic library has led to the identification and the subsequent characterization of nine denitrification gene clusters.

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 oí tfdA in the range 1 x 105 to 5 x 107 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. [ABSTRACT FROM AUTHOR]

The bioremediation of chloroethene contaminants in groundwater polluted systems is still a serious environmental challenge. Many previous studies have shown that cooperation of several dechlorinators is crucial for complete dechlorination of trichloroethene to ethene. In the present study, we used an explorative functional DNA microarray (DechloArray) to examine the composition of specific functional genes in groundwater samples in which chloroethene bioremediation was enhanced by delivery of hydrogen-releasing compounds. Our results demonstrate for the first time that complete biodegradation occurs through spatial and temporal variations of a wide diversity of dehalorespiring populations involving both Sulfurospirillum, Dehalobacter, Desulfitobacterium, Geobacter and Dehalococcoides genera. Sulfurospirillum appears to be the most active in the highly contaminated source zone, while Geobacter was only detected in the slightly contaminated downstream zone. The concomitant detection of both bvcA and vcrA genes suggests that at least two different Dehalococcoides species are probably responsible for the dechlorination of dichloroethenes and vinyl chloride to ethene. These species were not detected on sites where cis-dichloroethene accumulation was observed. These results support the notion that monitoring dechlorinators by the presence of specific functional biomarkers using a powerful tool such as DechloArray will be useful for surveying the efficiency of bioremediation strategies., (© 2012 The Authors. Microbial Biotechnology © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.)