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September 22, 2019

Melanization of mycorrhizal fungal necromass structures microbial decomposer communities

Mycorrhizal fungal necromass is increasingly recognized as an important contributor to soil organic carbon pools, particularly in forest ecosystems. While its decomposition rate is primarily determined by biochemical composition, how traits such as melanin content affect the structure of necromass decomposer communities remains poorly understood. To assess the role of biochemical traits on microbial decomposer community composition and functioning, we incubated melanized and non-melanized necromass of the mycorrhizal fungus Meliniomyces bicolor in Pinus- and Quercus-dominated forests in Minnesota, USA and then assessed the associated fungal and bacterial decomposer communities after 1, 2 and 3 months using high-throughput sequencing. Melanized necromass decomposed significantly slower than non-melanized necromass in both forests. The structure of the microbial decomposer communities depended significantly on necromass melanin content, although the effect was stronger for fungi than bacteria. On non-melanized necromass, fungal communities were dominated by r-selected ascomycete and mucoromycete microfungi early and then replaced by basidiomycete ectomycorrhizal fungi, while on melanized necromass these groups were co-dominant throughout the incubation. Bacterial communities were dominated by both specialist mycophageous and generalist taxa. Synthesis. Our results indicate that necromass biochemistry not only strongly affects rates of decomposition but also the structure of the associated decomposer communities. Furthermore, the observed colonization patterns suggest that fungi, and particularly ectomycorrhizal fungi, may play a more important role in necromass decomposition than previously recognized.

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September 22, 2019

Cow-to-mouse fecal transplantations suggest intestinal microbiome as one cause of mastitis.

Mastitis, which affects nearly all lactating mammals including human, is generally thought to be caused by local infection of the mammary glands. For treatment, antibiotics are commonly prescribed, which however are of concern in both treatment efficacy and neonate safety. Here, using bovine mastitis which is the most costly disease in the dairy industry as a model, we showed that intestinal microbiota alone can lead to mastitis.Fecal microbiota transplantation (FMT) from mastitis, but not healthy cows, to germ-free (GF) mice resulted in mastitis symptoms in mammary gland and inflammations in serum, spleen, and colon. Probiotic intake in parallel with FMT from diseased cows led to relieved mastitis symptoms in mice, by shifting the murine intestinal microbiota to a state that is functionally distinct from either healthy or diseased microbiota yet structurally similar to the latter. Despite conservation in mastitis symptoms, diseased cows and mice shared few mastitis-associated bacterial organismal or functional markers, suggesting striking divergence in mastitis-associated intestinal microbiota among lactating mammals. Moreover, an “amplification effect” of disease-health distinction in both microbiota structure and function was apparent during the cow-to-mouse FMT.Hence, dysbiosis of intestinal microbiota may be one cause of mastitis, and probiotics that restore intestinal microbiota function are an effective and safe strategy to treat mastitis.

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September 22, 2019

Transcriptome profiling of two ornamental and medicinal papaver herbs.

The Papaver spp. (Papaver rhoeas (Corn poppy) and Papaver nudicaule (Iceland poppy)) genera are ornamental and medicinal plants that are used for the isolation of alkaloid drugs. In this study, we generated 700 Mb of transcriptome sequences with the PacBio platform. They were assembled into 120,926 contigs, and 1185 (82.2%) of the benchmarking universal single-copy orthologs (BUSCO) core genes were completely present in our assembled transcriptome. Furthermore, using 128 Gb of Illumina sequences, the transcript expression was assessed at three stages of Papaver plant development (30, 60, and 90 days), from which we identified 137 differentially expressed transcripts. Furthermore, three co-occurrence heat maps are generated from 51 different plant genomes along with the Papaver transcriptome, i.e., secondary metabolite biosynthesis, isoquinoline alkaloid biosynthesis (BIA) pathway, and cytochrome. Sixty-nine transcripts in the BIA pathway along with 22 different alkaloids (quantified with LC-QTOF-MS/MS) were mapped into the BIA KEGG map (map00950). Finally, we identified 39 full-length cytochrome transcripts and compared them with other genomes. Collectively, this transcriptome data, along with the expression and quantitative metabolite profiles, provides an initial recording of secondary metabolites and their expression related to Papaver plant development. Moreover, these profiles could help to further detail the functional characterization of the various secondary metabolite biosynthesis and Papaver plant development associated problems.

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September 22, 2019

Isoform sequencing provides insight into natural genetic diversity in maize.

W64A, as a member of non-stiff stalk maize, has been used to develop current corn in plant breeding, and serving as one of broadest parent line for the commercial hybrid seed production (Huffman, 1984). The inbred had the characteristics of early flowering, average plant and ear height at its maturity, very strong roots and good stalks (Runge, 2004). In addition, W64A serves as an invaluable germplasm to study gene functions especially in the field of corn nutrition and endosperm texture given its nearly complete vitreousness and hardness (Figure 1a). However, little is known about the background of genetic and genomic information for W64A. With the advent of the revolutionary technology of PacBio long-read sequencing, we can simultaneously obtain a large amount of full-length cDNA up to 20 kb (An et al., 2018). This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.

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September 22, 2019

Evaluation of bacterial contamination in raw milk, ultra-high temperature milk and infant formula using single molecule, real-time sequencing technology.

The Pacific Biosciences (Menlo Park, CA) single molecule, real-time sequencing technology (SMRT) was reported to have some advantages in analyzing the bacterial profile of environmental samples. In this study, the presence of bacterial contaminants in raw milk, UHT milk, and infant formula was determined by SMRT sequencing of the full length 16S rRNA gene. The bacterial profiles obtained at different taxonomic levels revealed clear differences in bacterial community structure across the 16 analyzed dairy samples. No indicative pathogenic bacteria were found in any of these tested samples. However, some of the detected bacterial species (e.g., Bacillus cereus, Enterococcus casseliflavus, and Enterococcus gallinarum) might potentially relate with product quality defects and bacterial antibiotic gene transfer. Although only a limited number of dairy samples were analyzed here, our data have demonstrated for the first time the feasibility of using the SMRT sequencing platform in detecting bacterial contamination. Our paper also provides interesting reference information for future development of new precautionary strategies for controlling the dairy safety in large-scale industrialized production lines. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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September 22, 2019

Quantitative metaproteomics highlight the metabolic contributions of uncultured phylotypes in a thermophilic anaerobic digester.

In this study, we used multiple meta-omic approaches to characterize the microbial community and the active metabolic pathways of a stable industrial biogas reactor with food waste as the dominant feedstock, operating at thermophilic temperatures (60°C) and elevated levels of free ammonia (367 mg/liter NH3-N). The microbial community was strongly dominated (76% of all 16S rRNA amplicon sequences) by populations closely related to the proteolytic bacterium Coprothermobacter proteolyticus. Multiple Coprothermobacter-affiliated strains were detected, introducing an additional level of complexity seldom explored in biogas studies. Genome reconstructions provided metabolic insight into the microbes that performed biomass deconstruction and fermentation, including the deeply branching phyla Dictyoglomi and Planctomycetes and the candidate phylum “Atribacteria” These biomass degraders were complemented by a synergistic network of microorganisms that convert key fermentation intermediates (fatty acids) via syntrophic interactions with hydrogenotrophic methanogens to ultimately produce methane. Interpretation of the proteomics data also suggested activity of a Methanosaeta phylotype acclimatized to high ammonia levels. In particular, we report multiple novel phylotypes proposed as syntrophic acetate oxidizers, which also exert expression of enzymes needed for both the Wood-Ljungdahl pathway and ß-oxidation of fatty acids to acetyl coenzyme A. Such an arrangement differs from known syntrophic oxidizing bacteria and presents an interesting hypothesis for future studies. Collectively, these findings provide increased insight into active metabolic roles of uncultured phylotypes and presents new synergistic relationships, both of which may contribute to the stability of the biogas reactor.Biogas production through anaerobic digestion of organic waste provides an attractive source of renewable energy and a sustainable waste management strategy. A comprehensive understanding of the microbial community that drives anaerobic digesters is essential to ensure stable and efficient energy production. Here, we characterize the intricate microbial networks and metabolic pathways in a thermophilic biogas reactor. We discuss the impact of frequently encountered microbial populations as well as the metabolism of newly discovered novel phylotypes that seem to play distinct roles within key microbial stages of anaerobic digestion in this stable high-temperature system. In particular, we draft a metabolic scenario whereby multiple uncultured syntrophic acetate-oxidizing bacteria are capable of syntrophically oxidizing acetate as well as longer-chain fatty acids (via the ß-oxidation and Wood-Ljundahl pathways) to hydrogen and carbon dioxide, which methanogens subsequently convert to methane. Copyright © 2016 American Society for Microbiology.

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September 22, 2019

Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome.

Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested.Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes.MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.

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September 22, 2019

Recent developments in using advanced sequencing technologies for the genomic studies of lignin and cellulose degrading microorganisms.

Lignin is a complex polyphenyl aromatic compound which exists in tight associations with cellulose and hemicellulose to form plant primary and secondary cell wall. Lignocellulose is an abundant renewable biomaterial present on the earth. It has gained much attention in the scientific community in recent years because of its potential applications in bio-based industries. Microbial degradation of lignocellulose polymers was well studied in wood decaying fungi. Based on the plant materials they degrade these fungi were classified as white rot, brown rot and soft rot. However, some groups of bacteria belonging to the actinomycetes, a-proteobacteria and ß-proteobacteria were also found to be efficient in degrading lignocellulosic biomass but not well understood unlike the fungi. In this review we focus on recent advancements deployed for finding and understanding the lignocellulose degradation by microorganisms. Conventional molecular methods like sequencing 16s rRNA and Inter Transcribed Spacer (ITS) regions were used for identification and classification of microbes. Recent progression in genomics mainly next generation sequencing technologies made the whole genome sequencing of microbes possible in a great ease. The whole genome sequence studies reveals high quality information about genes and canonical pathways involved in the lignin and other cell wall components degradation.

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September 22, 2019

Alternative isoform analysis of Ttc8 expression in the rat pineal gland using a multi-platform sequencing approach reveals neural regulation.

Alternative isoform regulation (AIR) vastly increases transcriptome diversity and plays an important role in numerous biological processes and pathologies. However, the detection and analysis of isoform-level differential regulation is difficult, particularly in the face of complex and incompletely-annotated transcriptomes. Here we have used Illumina short-read/high-throughput RNA-Seq to identify 55 genes that exhibit neurally-regulated AIR in the pineal gland, and then used two other complementary experimental platforms to further study and characterize the Ttc8 gene, which is involved in Bardet-Biedl syndrome and non-syndromic retinitis pigmentosa. Use of the JunctionSeq analysis tool led to the detection of several novel exons and splice junctions in this gene, including two novel alternative transcription start sites which were found to display disproportionately strong neurally-regulated differential expression in several independent experiments. These high-throughput sequencing results were validated and augmented via targeted qPCR and long-read Pacific Biosciences SMRT sequencing. We confirmed the existence of numerous novel splice junctions and the selective upregulation of the two novel start sites. In addition, we identified more than 20 novel isoforms of the Ttc8 gene that are co-expressed in this tissue. By using information from multiple independent platforms we not only greatly reduce the risk of errors, biases, and artifacts influencing our results, we also are able to characterize the regulation and splicing of the Ttc8 gene more deeply and more precisely than would be possible via any single platform. The hybrid method outlined here represents a powerful strategy in the study of the transcriptome.

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September 22, 2019

Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells.

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for =200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.

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September 22, 2019

A quantitative SMRT cell sequencing method for ribosomal amplicons.

Advances in sequencing technologies continue to provide unprecedented opportunities to characterize microbial communities. For example, the Pacific Biosciences Single Molecule Real-Time (SMRT) platform has emerged as a unique approach harnessing DNA polymerase activity to sequence template molecules, enabling long reads at low costs. With the aim to simultaneously classify and enumerate in situ microbial populations, we developed a quantitative SMRT (qSMRT) approach that involves the addition of exogenous standards to quantify ribosomal amplicons derived from environmental samples. The V7-9 regions of 18S SSU rDNA were targeted and quantified from protistan community samples collected in the Ross Sea during the Austral summer of 2011. We used three standards of different length and optimized conditions to obtain accurate quantitative retrieval across the range of expected amplicon sizes, a necessary criterion for analyzing taxonomically diverse 18S rDNA molecules from natural environments. The ability to concurrently identify and quantify microorganisms in their natural environment makes qSMRT a powerful, rapid and cost-effective approach for defining ecosystem diversity and function. Copyright © 2017 Elsevier B.V. All rights reserved.

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September 22, 2019

Evaluation of long-term performance of sediment microbial fuel cells and the role of natural resources

Sediment microbial fuel cells (SMFCs) are expected to be used as a renewable power source for remote environmental monitoring; therefore, evaluation of their long-term power performance is critical for their usability. In this paper, we present novel data needed to understand the long-term performance of SMFCs. We used 3-D Microemulsion (3DMe)™ doped anodes, which slowly release lactate and its fermented products. During our tests, anode-limited SMFCs with and without 3DMe-doped anodes were operated for more than 18 months with a load simulating a sensor operation. We found that doping an anode with an electron donor reduced startup time and increased maximum power (55 ± 2 µW compared to 46 ± 2 µW) in the control systems. We found that the long-term steady power performance is approximately 33% of the maximum power (~18 µW). Finally, our small-sized SMFCs generated higher power densities than those in the literature (28 mW/m2 versus 4 mW/m2). Using electron donor doped anodes can be practical when a short startup time and initial high power are needed. However, if long-term power is critical, the addition of an electron donor does not provide a practical advantage. In addition, in long-term operation enrichment of the anode surface with electrochemically active bacteria does not provide any advantage.

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September 22, 2019

Shannon: an information-optimal de novo RNA-Seq assembler

De novo assembly of short RNA-Seq reads into transcripts is challenging due to sequence similarities in transcriptomes arising from gene duplications and alternative splicing of transcripts. We present Shannon, an RNA-Seq assembler with an optimality guarantee derived from principles of information theory: Shannon reconstructs nearly all information-theoretically reconstructable transcripts. Shannon is based on a theory we develop for de novo RNA-Seq assembly that reveals differing abundances among transcripts to be the key, rather than the barrier, to effective assembly. The assembly problem is formulated as a sparsest-flow problem on a transcript graph, and the heart of Shannon is a novel iterative flow-decomposition algorithm. This algorithm provably solves the information-theoretically reconstructable instances in linear-time even though the general sparsest-flow problem is NP-hard. Shannon also incorporates several additional new algorithmic advances: a new error-correction algorithm based on successive cancelation, a multi-bridging algorithm that carefully utilizes read information in the k-mer de Bruijn graph, and an approximate graph partitioning algorithm to split the transcriptome de Bruijn graph into smaller components. In tests on large RNA-Seq datasets, Shannon obtains significant increases in sensitivity along with improvements in specificity in comparison to state-of-the-art assemblers.

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September 22, 2019

High-quality reference transcript datasets hold the key to transcript-specific RNA-sequencing analysis in plants.

Re-programming of the transcriptome involves both transcription and alternative splicing (AS). Some genes are regulated only at the AS level with no change in expression at the gene level. AS data must be incorporated as an essential aspect of the regulation of gene expression. RNA-sequencing (RNA-seq) can deliver both transcriptional and AS information, but accurate methods to analyse the added complexity in RNA-seq data are needed. The construction of a comprehensive reference transcript dataset (RTD) for a specific plant species, variety or accession, from all available sequence data, will immediately allow more robust analysis of RNA-seq data. RTDs will continually evolve and improve, a process that will be more efficient if resources across a community are shared and pooled.© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

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September 22, 2019

Improving eukaryotic genome annotation using single molecule mRNA sequencing.

The advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq.We sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features.Overall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.

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