Metagenome from a Spirulina digesting biogas reactor: analysis via binning of contigs and classification of short reads

Sulfate reduction behavior in response to landfill dynamic pressure changes

During the long-term stabilization process of landfills, the pressure field undergoes constant changes. This study constructed dynamic pressure changes scenarios of high-pressure differentials (0.6 MPa) and low-pressure differentials (0.2 MPa) in the landfill pressure field at 25 °C and 50 °C, and investigated the sulfate reduction behavior in response to landfill dynamic pressure changes. The results showed that the pressurization or depressurization of high-pressure differentials caused more significant differences in sulfate reduction behavior than that of low-pressure differentials. The lowest hydrogen sulfide (H2S) release peak concentration under pressurization was only 29.67% of that under initial pressure condition; under depressurization, the highest peak concentration of H2S was up to 21,828 mg m-3, posing a serious risk of H2S pollution. Microbial community and correlation analysis showed that pressure had a negative impact on the sulfate-reducing bacteria (SRB) community, and the SRB community adjusted its structure to adapt to pressure changes. Specific SRBs were further enriched with pressure changes. Differential H2S release behavior under pressure changes in the 25 °C pressure environments were mediated by Desulfofarcimen (ASV343) and Desulfosporosinus (ASV1336), while Candidatus Desulforudis (ASV24) and Desulfohalotomaculum (ASV94) played a key role at 50 °C. This study is helpful in the formulation of control strategies for the source of odor pollution in landfills.

Biomethane production and microbial strategies corresponding to high organic loading treatment for molasses wastewater in an upflow anaerobic filter reactor

Molasses wastewater contains high levels of organic compounds, cations, and anions, causing operational problems for anaerobic biological treatment. In this study, an upflow anaerobic filter (UAF) reactor was employed to establish a high organic loading treatment system for molasses wastewater and further investigated the microbial community dynamics in response to this stressful operation. The biogas production increased with an increase in total organic carbon (TOC) loading rate from 1.0 to 14 g/L/day, and then it decreased with further TOC loading rate addition until 16 g/L/day. The UAF reactor achieved a maximum biogas production of 6800 mL/L/day with a TOC removal efficiency of 66.5% at a TOC loading rate of 14 g/L/day. Further microbial analyses revealed that both the bacterial and archaeal communities developed multiple strategies to maintain stable operation of the reactor at high organic loading (e.g., Proteiniphilum and Defluviitoga maintained high abundances throughout the operation; Tissierella temporarily dominated the bacterial community at TOC loading rates of 8.0 to 14 g/L/day; and multi-trophic Methanosarcina shifted as the dominant methanogen at the TOC loading rates of 8.0 to 16 g/L/day). This study presents insights into a high organic loading molasses wastewater treatment system and the microbial flexibility in methane fermentation in response to process disturbances.

Anaerobic co-digestion of thermo-alkaline pretreated microalgae and sewage sludge: Methane potential and microbial community

To improve methane production from sewage sludge (SS), co-digestion of SS and microalgae (MA) was studied and the application of thermo-alkaline pretreatment to MA was evaluated. The results showed that thermo-alkaline pretreatment at 90°C for 120 min on MA was the optimum pretreatment condition. Furthermore, when the volatile solids (VS) ratio of SS and MA was 1:2, the methane yield reached maximum (368.94 mL/g VS). Fourier transform infrared (FT-IR) and thermogravimetric analysis confirmed the synergetic effects of thermo-alkaline pretreated MA on its co-digestion with SS. The analyses of microbial community indicated that Methanobacterium and Methanosarcina were the dominant methanogens during the co-digestion process. However, the relative abundance of Methanosarcina in thermo-alkaline pretreated groups was higher compared to unpretreated groups. The microbial community structure might be affected by thermo-alkaline pretreatment rather than by the MA dosage in the co-digestion.

Activity-based, genome-resolved metagenomics uncovers key populations and pathways involved in subsurface conversions of coal to methane

Microbial metabolisms and interactions that facilitate subsurface conversions of recalcitrant carbon to methane are poorly understood. We deployed an in situ enrichment device in a subsurface coal seam in the Powder River Basin (PRB), USA, and used BONCAT-FACS-Metagenomics to identify translationally active populations involved in methane generation from a variety of coal-derived aromatic hydrocarbons. From the active fraction, high-quality metagenome-assembled genomes (MAGs) were recovered for the acetoclastic methanogen, Methanothrix paradoxum, and a novel member of the Chlorobi with the potential to generate acetate via the Pta-Ack pathway. Members of the Bacteroides and Geobacter also encoded Pta-Ack and together, all four populations had the putative ability to degrade ethylbenzene, phenylphosphate, phenylethanol, toluene, xylene, and phenol. Metabolic reconstructions, gene analyses, and environmental parameters also indicated that redox fluctuations likely promote facultative energy metabolisms in the coal seam. The active "Chlorobi PRB" MAG encoded enzymes for fermentation, nitrate reduction, and multiple oxygenases with varying binding affinities for oxygen. "M. paradoxum PRB" encoded an extradiol dioxygenase for aerobic phenylacetate degradation, which was also present in previously published Methanothrix genomes. These observations outline underlying processes for bio-methane from subbituminous coal by translationally active populations and demonstrate activity-based metagenomics as a powerful strategy in next generation physiology to understand ecologically relevant microbial populations.

Effect of different microbial seeds on batch anaerobic digestion of fish waste

Initial microbial compositions would be the precursor for the efficient anaerobic digestion (AD) of fish waste (FW). A mesophilic batch test was conducted using four seeds collected from different digesters treating various combinations of substrates to investigate their effects on FW degradation. Key microbial groups were identified by 16s rRNA gene-based metagenomics analysis. Among four, the seed from the digester co-digesting livestock manure, food waste, and food wastewater showed the best performance and obtained the highest methane yield (350.5 ± 5.2 mL/gVS_added) and lowest lag phase (0.6 ± 0.1 d). Proteiniphilum, Aminobacterium, dgA-11 gut group, and Syntrophomonas were dominant bacterial genera identified in FW degradation. Methanosaeta was the dominant methanogen in the best performing seed and microbial network analysis revealed its contribution to achieving the highest CH₄ yield. Obtained results could be useful in selecting microbial seed sources to avoid system imbalance in full-scale digesters that treat FW.

GraphBin: refined binning of metagenomic contigs using assembly graphs

MOTIVATION

The field of metagenomics has provided valuable insights into the structure, diversity and ecology within microbial communities. One key step in metagenomics analysis is to assemble reads into longer contigs which are then binned into groups of contigs that belong to different species present in the metagenomic sample. Binning of contigs plays an important role in metagenomics and most available binning algorithms bin contigs using genomic features such as oligonucleotide/k-mer composition and contig coverage. As metagenomic contigs are derived from the assembly process, they are output from the underlying assembly graph which contains valuable connectivity information between contigs that can be used for binning.

RESULTS

We propose GraphBin, a new binning method that makes use of the assembly graph and applies a label propagation algorithm to refine the binning result of existing tools. We show that GraphBin can make use of the assembly graphs constructed from both the de Bruijn graph and the overlap-layout-consensus approach. Moreover, we demonstrate improved experimental results from GraphBin in terms of identifying mis-binned contigs and binning of contigs discarded by existing binning tools. To the best of our knowledge, this is the first time that the information from the assembly graph has been used in a tool for the binning of metagenomic contigs.

AVAILABILITY AND IMPLEMENTATION

The source code of GraphBin is available at https://github.com/Vini2/GraphBin.

CONTACT

vijini.mallawaarachchi@anu.edu.au or yu.lin@anu.edu.au.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae

"Omics" represent a combinatorial approach to high-throughput analysis of biological entities for various purposes. It broadly encompasses genomics, transcriptomics, proteomics, lipidomics, and metabolomics. Bacteria and microalgae exhibit a wide range of genetic, biochemical and concomitantly, physiological variations owing to their exposure to biotic and abiotic dynamics in their ecosystem conditions. Consequently, optimal conditions for adequate growth and production of useful bacterial or microalgal metabolites are critically unpredictable. Traditional methods employ microbe isolation and 'blind'-culture optimization with numerous chemical analyses making the bioprospecting process laborious, strenuous, and costly. Advances in the next generation sequencing (NGS) technologies have offered a platform for the pan-genomic analysis of microbes from community and strain downstream to the gene level. Changing conditions in nature or laboratory accompany epigenetic modulation, variation in gene expression, and subsequent biochemical profiles defining an organism's inherent metabolic repertoire. Proteome and metabolome analysis could further our understanding of the molecular and biochemical attributes of the microbes under research. This review provides an overview of recent studies that have employed omics as a robust, broad-spectrum approach for screening bacteria and microalgae to exploit their potential as sources of drug leads by focusing on their genomes, secondary metabolite biosynthetic pathway genes, transcriptomes, and metabolomes. We also highlight how recent studies have combined molecular biology with analytical chemistry methods, which further underscore the need for advances in bioinformatics and chemoinformatics as vital instruments in the discovery of novel bacterial and microalgal strains as well as new drug leads.

Efficient nitrous oxide recovery from incineration leachate by a nosZ-deficient strain of Pseudomonas aeruginosa

In this study, nitrous oxide was recovered from a lab-scale moving-bed biofilm reactor (MBBR) treating partial nitrification-treated leachate supplemented with a nosZ-deficient strain of Pseudomonas aeruginosa. Batch culture tests with the nosZ-deficient strain determined that the threshold for free nitrous acid (FNA) inhibition was 0.016 mg/L and that FNA concentrations above this threshold severely inhibited denitrification and transcription of genes from the dissimilatory nitrate reduction pathway (narG, nirS, and norB). High nitrite removal and N₂O conversion efficiencies (>95%) were achieved with long-term operation of this MBBR. N₂O accounted for the majority of biogas (80%) produced when the MBBR was fed partial nitrification-treated leachate with high nitrite concentrations and the drainage ratio was adjusted to 30%. Bacterial community analysis revealed that the nosZ-deficient Pseudomonas strain remained metabolically active and was primarily responsible for denitrification processes in the reactor. This study presents a promising method for N₂O recovery from incineration leachate.

Transition of microbial community structures after development of membrane fouling in membrane bioreactors (MBRs)

Although membrane fouling is a major issue when operating membrane bioreactors (MBRs), information regarding MBR performance and the sludge microbiome after the development of fouling remains limited. For the present study, two MBRs were operated for approximately 1 month under conditions of membrane fouling to investigate the effects of highly stressed environments on the sludge microbiome. After the development of fouling, a Collimonas-related operational taxonomic unit (OTU) was highly dominant in both reactors (relative abundances were ⁓ 63%) and this predomination caused a precipitous decline in the diversity indices of the sludge microbiomes. Because the excessive predomination by limited numbers of OTUs can lead to reductions in the adaptability to environmental changes, monitoring microbial diversity may be a valuable indicator for maintaining the robustness of a sludge microbiome. While, the decrease in the abundance of the Collimonas-related OTU resulted in the predomination of distinct microorganisms in each of the reactors despite being operated under the same conditions; this finding indicates existence of strong pressure to perturb the microbiomes. Detailed analyses suggested that the availability of terminal electron acceptors and competitive interactions between microbes via the secretion of extracellular proteins appeared to differentiate the structures of the respective microbial communities. During the extracellular proteins were secreted in the sludge, considerable portion of microbes were dead and large amounts of biomolecules seemed to be released; resultantly facilitated the predomination of fermentative anaerobes in one reactor as they use organic substances but not inorganic terminal electron acceptors to generate ATP under anaerobic conditions.

BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage

Motivation

Metagenomics investigates the DNA sequences directly recovered from environmental samples. It often starts with reads assembly, which leads to contigs rather than more complete genomes. Therefore, contig binning methods are subsequently used to bin contigs into genome bins. While some clustering-based binning methods have been developed, they generally suffer from problems related to stability and robustness.

Results

We introduce BMC3C, an ensemble clustering-based method, to accurately and robustly bin contigs by making use of DNA sequence Composition, Coverage across multiple samples and Codon usage. BMC3C begins by searching the proper number of clusters and repeatedly applying the k-means clustering with different initializations to cluster contigs. Next, a weight graph with each node representing a contig is derived from these clusters. If two contigs are frequently grouped into the same cluster, the weight between them is high, and otherwise low. BMC3C finally employs a graph partitioning technique to partition the weight graph into subgraphs, each corresponding to a genome bin. We conduct experiments on both simulated and real-world datasets to evaluate BMC3C, and compare it with the state-of-the-art binning tools. We show that BMC3C has an improved performance compared to these tools. To our knowledge, this is the first time that the codon usage features and ensemble clustering are used in metagenomic contig binning.

Availability and implementation

The codes of BMC3C are available at http://mlda.swu.edu.cn/codes.php?name=BMC3C.

Supplementary information

Supplementary data are available at Bioinformatics online.

Effect of long residence time and high temperature over anaerobic biodegradation of Scenedesmus microalgae grown in wastewater

Anaerobic digestion of indigenous Scenedesmus spp. microalgae was studied in continuous lab-scale anaerobic reactors at different temperatures (35 °C and 55 °C), and sludge retention time - SRT (50 and 70 days). Mesophilic digestion was performed in a continuous stirred-tank reactor (CSTR) and in an anaerobic membrane bioreactor (AnMBR). Mesophilic CSTR operated at 50 days SRT only achieved 11.9% of anaerobic biodegradability whereas in the AnMBR at 70 days SRT and 50 days HRT reached 39.5%, which is even higher than the biodegradability achieved in the thermophilic CSTR at 50 days SRT (30.4%). Microbial analysis revealed a high abundance of cellulose-degraders in both reactors, AnMBR (mainly composed of 9.4% Bacteroidetes, 10.1% Chloroflexi, 8.0% Firmicutes and 13.2% Thermotogae) and thermophilic CSTR (dominated by 23.8% Chloroflexi and 12.9% Firmicutes). However, higher microbial diversity was found in the AnMBR compared to the thermophilic CSTR which is related to the SRT. since high SRT promoted low growth-rate microorganisms, increasing the hydrolytic potential of the system. These results present the membrane technology as a promising approach to revalue microalgal biomass, suggesting that microalgae biodegradability and consequently the methane production could be improved operating at higher SRT.

Microbial communities of biomethanization digesters fed with raw and heat pre-treated microalgae biomasses

Microalgae biomasses are considered promising feedstocks for biofuel and methane productions. Two Continuously Stirred Tank Reactors (CSTR), fed with fresh (CSTR-C) and heat pre-treated (CSTR-T) Chlorella biomass were run in parallel in order to determine methane productions. The methane yield was 1.5 times higher in CSTR-T with regard to CSTR-C. Aiming to understand the microorganism roles within of the reactors, the sludge used as an inoculum (I), plus raw (CSTR-C) and heat pre-treated (CSTR-T) samples were analyzed by high-throughput pyrosequencing. The bacterial communities were dominated by Proteobacteria, Bacteroidetes, Chloroflexi and Firmicutes. Spirochaetae and Actinobacteria were only detected in sample I. Proteobacteria, mainly Alfaproteobacteria, were by far the dominant phylum within of the CSTR-C bioreactor. Many of the sequences retrieved were related to bacteria present in activated sludge treatment plants and they were absent after thermal pre-treatment. Most of the sequences affiliated to the Bacteroidetes were related to uncultured groups. Anaerolineaceae was the sole family found of the Chloroflexi phylum. All of the genera identified of the Firmicutes phylum carried out macromolecule hydrolysis and by-product fermentation. The proteolytic bacteria were prevalent over the saccharolytic microbes. The percentage of the proteolytic genera increased from the inoculum to the CSTR-T sample in a parallel fashion with an available protein increase owing to the high protein content of Chlorella. To relate the taxa identified by high-throughput sequencing to their functional roles remains a future challenge.