The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning ...approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments.
MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license.
Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel ...iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://github.com/csmiller/EMIRGE.
Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered ...microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.
Microorganisms in the subsurface represent a substantial but poorly understood component of the Earth's biosphere. Subsurface environments are complex and difficult to characterize; thus, their ...microbiota have remained as a 'dark matter' of the carbon and other biogeochemical cycles. Here we deeply sequence two sediment-hosted microbial communities from an aquifer adjacent to the Colorado River, CO, USA. No single organism represents more than ~1% of either community. Remarkably, many bacteria and archaea in these communities are novel at the phylum level or belong to phyla lacking a sequenced representative. The dominant organism in deeper sediment, RBG-1, is a member of a new phylum. On the basis of its reconstructed complete genome, RBG-1 is metabolically versatile. Its wide respiration-based repertoire may enable it to respond to the fluctuating redox environment close to the water table. We document extraordinary microbial novelty and the importance of previously unknown lineages in sediment biogeochemical transformations.
Recovering individual genomes from metagenomic datasets allows access to uncultivated microbial populations that may have important roles in natural and engineered ecosystems. Understanding the roles ...of these uncultivated populations has broad application in ecology, evolution, biotechnology and medicine. Accurate binning of assembled metagenomic sequences is an essential step in recovering the genomes and understanding microbial functions.
We have developed a binning algorithm, MaxBin, which automates the binning of assembled metagenomic scaffolds using an expectation-maximization algorithm after the assembly of metagenomic sequencing reads. Binning of simulated metagenomic datasets demonstrated that MaxBin had high levels of accuracy in binning microbial genomes. MaxBin was used to recover genomes from metagenomic data obtained through the Human Microbiome Project, which demonstrated its ability to recover genomes from real metagenomic datasets with variable sequencing coverages. Application of MaxBin to metagenomes obtained from microbial consortia adapted to grow on cellulose allowed genomic analysis of new, uncultivated, cellulolytic bacterial populations, including an abundant myxobacterial population distantly related to Sorangium cellulosum that possessed a much smaller genome (5 MB versus 13 to 14 MB) but has a more extensive set of genes for biomass deconstruction. For the cellulolytic consortia, the MaxBin results were compared to binning using emergent self-organizing maps (ESOMs) and differential coverage binning, demonstrating that it performed comparably to these methods but had distinct advantages in automation, resolution of related genomes and sensitivity.
The automatic binning software that we developed successfully classifies assembled sequences in metagenomic datasets into recovered individual genomes. The isolation of dozens of species in cellulolytic microbial consortia, including a novel species of myxobacteria that has the smallest genome among all sequenced aerobic myxobacteria, was easily achieved using the binning software. This work demonstrates that the processes required for recovering genomes from assembled metagenomic datasets can be readily automated, an important advance in understanding the metabolic potential of microbes in natural environments. MaxBin is available at https://sourceforge.net/projects/maxbin/.
Some soil fungi in the Leotiomycetes form ericoid mycorrhizal (ERM) symbioses with Ericaceae. In the harsh habitats in which they occur, ERM plant survival relies on nutrient mobilization from soil ...organic matter (SOM) by their fungal partners. The characterization of the fungal genetic machinery underpinning both the symbiotic lifestyle and SOM degradation is needed to understand ERM symbiosis functioning and evolution, and its impact on soil carbon (C) turnover.
We sequenced the genomes of the ERM fungi Meliniomyces bicolor, M. variabilis, Oidiodendron maius and Rhizoscyphus ericae, and compared their gene repertoires with those of fungi with different lifestyles (ecto- and orchid mycorrhiza, endophytes, saprotrophs, pathogens). We also identified fungal transcripts induced in symbiosis.
The ERM fungal gene contents for polysaccharide-degrading enzymes, lipases, proteases and enzymes involved in secondary metabolism are closer to those of saprotrophs and pathogens than to those of ectomycorrhizal symbionts. The fungal genes most highly upregulated in symbiosis are those coding for fungal and plant cell wall-degrading enzymes (CWDEs), lipases, proteases, transporters and mycorrhiza-induced small secreted proteins (MiSSPs).
The ERM fungal gene repertoire reveals a capacity for a dual saprotrophic and biotrophic lifestyle. This may reflect an incomplete transition from saprotrophy to the mycorrhizal habit, or a versatile life strategy similar to fungal endophytes.
•White-rot basidiomycetes are promising sources of cellulases and xylanases.•Irpex lacteus and Schizophyllum commune showed compatible interaction.•Availability of carbon source determined outcomes ...of interspecific interaction.•Co-culture conditions optimization improved hydrolases production.•Synergistic enzyme preparation exhibited 11% higher hydrolysis of biomass.
Mono and dual cultures of four white-rot basidiomycete species were evaluated for cellulase and xylanase activity under submerged fermentation conditions. Co-cultivation of Pycnoporus coccineus or Trametes hirsuta with Schizophyllum commune displayed antagonistic interactions resulting in the decrease of endoglucanase and total cellulase activities. In contrast, increases in cellulase and xylanase activity were revealed through the compatible interactions of Irpex lacteus with S. commune. Co-cultivation conditions were optimized for maximum enzyme production by I. lacteus and S. commune, the best producers of cellulase/xylanase and β-glucosidase, respectively. An optimized medium for the target enzyme production by the mixed culture was established in a laboratory fermenter yielding 7U/mL total cellulase, 142U/mL endoglucanase, 104U/mL xylanase, and 5.2U/mL β-glucosidase. The dual culture approach resulted in an enzymatic mixture with 11% improved lignocellulose saccharification potential compared to enzymes from a monoculture of I. lacteus.
The future bioeconomy promises drop-in or performance-advantaged biofuels and bioproducts derived from lignocellulosic biomass, substantial greenhouse gas emissions reductions in sectors with few or ...no alternatives, and increased domestic energy production in countries with sufficient biomass resources. Despite the slower than anticipated pace of commercializing next-generation biofuels, the research community continues to make dramatic improvements at every stage of production, from feedstock cultivation through conversion to final products. However, the interdisciplinary nature of bioenergy research, and the need for cross-coordination among biologists, chemists, agronomists, and engineers, make coordinating and optimizing these strategies challenging. This Perspective surveys recent advancements in bioenergy crop engineering, lignocellulosic biomass deconstruction and fractionation, catabolism of biomass-derived sugars and aromatics, and biological conversion to fuels and products. We organize major research approaches into broad categories and comment on which strategies offer synergies or trade-offs in the context of four approaches to improving the economics and carbon-efficiency of advanced biofuels and bioproducts: (1) maximize sugar conversion to a single product, (2) utilize diverse carbon sources for producing a single product, (3) convert lignin to high-value products, and (4) fractionate the hydrolysate to derive maximum value from each component.
Machine learning for metabolic engineering: A review Lawson, Christopher E.; Martí, Jose Manuel; Radivojevic, Tijana ...
Metabolic engineering,
January 2021, 2021-01-00, 20210101, 2021-01-01, Letnik:
63, Številka:
C
Journal Article
Recenzirano
Odprti dostop
Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to ...metabolic engineers, as well as providing in-depth illustrative examples leveraging omics data and improving production. We also include practical advice for the practitioner in terms of data management, algorithm libraries, computational resources, and important non-technical issues. A variety of applications ranging from pathway construction and optimization, to genetic editing optimization, cell factory testing, and production scale-up are discussed. Moreover, the promising relationship between machine learning and mechanistic models is thoroughly reviewed. Finally, the future perspectives and most promising directions for this combination of disciplines are examined.
•In this review, we offer an introduction to Machine learning in terms that are relatable to metabolic engineers.•We include practical advice for the practitioner in terms of data management, algorithm libraries, and computational resources.•A variety of applications ranging from pathway construction and optimization, to scale-up are discussed.•Finally, the future perspectives and most promising directions for this combination of disciplines are examined.
High-solids incubations were performed to enrich for microbial communities and enzymes that decompose rice straw under mesophilic (35°C) and thermophilic (55°C) conditions. Thermophilic enrichments ...yielded a community that was 7.5 times more metabolically active on rice straw than mesophilic enrichments. Extracted xylanase and endoglucanse activities were also 2.6 and 13.4 times greater, respectively, for thermophilic enrichments. Metagenome sequencing was performed on enriched communities to determine community composition and mine for genes encoding lignocellulolytic enzymes. Proteobacteria were found to dominate the mesophilic community while Actinobacteria were most abundant in the thermophilic community. Analysis of protein family representation in each metagenome indicated that cellobiohydrolases containing carbohydrate binding module 2 (CBM2) were significantly overrepresented in the thermophilic community. Micromonospora, a member of Actinobacteria, primarily housed these genes in the thermophilic community. In light of these findings, Micromonospora and other closely related Actinobacteria genera appear to be promising sources of thermophilic lignocellulolytic enzymes for rice straw deconstruction under high-solids conditions. Furthermore, these discoveries warrant future research to determine if exoglucanases with CBM2 represent thermostable enzymes tolerant to the process conditions expected to be encountered during industrial biofuel production.
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