Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources

Evidence for Novel Hepaciviruses in Rodents

Hepatitis C virus (HCV) is among the most relevant causes of liver cirrhosis and hepatocellular carcinoma. Research is complicated by a lack of accessible small animal models. The systematic investigation of viruses of small mammals could guide efforts to establish such models, while providing insight into viral evolutionary biology. We have assembled the so-far largest collection of small-mammal samples from around the world, qualified to be screened for bloodborne viruses, including sera and organs from 4,770 roden

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources

Evaluation of Two Methods to Concentrate SARS-CoV-2 from Untreated Wastewater

Use of wastewater-based epidemiology as a tool to record and manage the course of SARS-CoV-2 infections in human populations requires information about the efficiency of methods to concentrate the virus from wastewater. In the present study, we spiked untreated wastewater with quantified SARS-CoV-2 positive clinical material and enriched the virus by polyethylene glycol precipitation and ultrafiltration with Vivaspin 10 kDa MWCO columns. SARS-CoV-2 was detected and quantified by reverse transcription quantitative PCR (E- and S-gene) and droplet digital PCR. The concentration of virus with precipitation resulted in mean recoveries between 59.4% and 63.7% whereas rates from 33.0% to 42.6% after ultrafiltration of samples were demonstrated. The results suggest that the use of both methods allows an effective and practicable enrichment of SARS-CoV-2 from raw wastewater

Data_Sheet_1_Whole-genome sequence of the filamentous diazotrophic cyanobacterium Tolypothrix sp. PCC 7712 and its comparison with non-diazotrophic Tolypothrix sp. PCC 7601.pdf

Cyanobacteria are highly promising microorganisms in forthcoming biotechnologies. Besides the systematic development of molecular tools for genetic engineering, the design of chassis strains and novel reactor concepts are in focus. The latter includes capillary biofilm reactors (CBR), which offer a high surface area-to-volume ratio and very high cell densities. In this context, Tolypothrix sp. PCC 7712 was found to be highly suited for this reactor system due to maximal surface coverage, extraordinarily strong biofilm attachment, and high biomass formation. Here, we provide the genome sequence of Tolypothrix sp. PCC 7712 to potentially allow targeted strain engineering. Surprisingly, it was almost identical to an available incomplete genome draft of Tolypothrix sp. PCC 7601. Thus, we completely sequenced this strain as well and compared it in detail to strain PCC 7712. Comparative genome analysis revealed 257 and 80 unique protein-coding sequences for strains PCC 7601 and PCC 7712, respectively. Clustering genomes based on average nucleotide identity (ANI) and 16S rRNA homology showed 99.98% similarity and only minor distance, respectively, between the two strains in contrast to 21 other cyanobacterial genomes. Despite these high similarities, both strains differ in the ability to fix atmospheric nitrogen and show specific sequence variations, which are discussed in the paper.</p

Table_1_Whole-genome sequence of the filamentous diazotrophic cyanobacterium Tolypothrix sp. PCC 7712 and its comparison with non-diazotrophic Tolypothrix sp. PCC 7601.xlsx

Cyanobacteria are highly promising microorganisms in forthcoming biotechnologies. Besides the systematic development of molecular tools for genetic engineering, the design of chassis strains and novel reactor concepts are in focus. The latter includes capillary biofilm reactors (CBR), which offer a high surface area-to-volume ratio and very high cell densities. In this context, Tolypothrix sp. PCC 7712 was found to be highly suited for this reactor system due to maximal surface coverage, extraordinarily strong biofilm attachment, and high biomass formation. Here, we provide the genome sequence of Tolypothrix sp. PCC 7712 to potentially allow targeted strain engineering. Surprisingly, it was almost identical to an available incomplete genome draft of Tolypothrix sp. PCC 7601. Thus, we completely sequenced this strain as well and compared it in detail to strain PCC 7712. Comparative genome analysis revealed 257 and 80 unique protein-coding sequences for strains PCC 7601 and PCC 7712, respectively. Clustering genomes based on average nucleotide identity (ANI) and 16S rRNA homology showed 99.98% similarity and only minor distance, respectively, between the two strains in contrast to 21 other cyanobacterial genomes. Despite these high similarities, both strains differ in the ability to fix atmospheric nitrogen and show specific sequence variations, which are discussed in the paper.</p

Phylogenetic analysis of a newfound bat-borne hantavirus supports a laurasiatherian host association for ancestral mammalian hantaviruses

Until recently, hantaviruses (family Bunyaviridae) were believed to originate from rodent reservoirs. However, genetically distinct hantaviruses were lately found in shrews and moles, as well as in bats from Africa and Asia. Bats (order Chiroptera) are considered important reservoir hosts for emerging human pathogens. Here, we report on the identification of a novel hantavirus, provisionally named Makokou virus (MAKV), in Noack's Roundleaf Bat (Hipposideros ruber) in Gabon, Central Africa. Phylogenetic analysis of the genomic L-segment showed that MAKV was the most closely related to other bat-borne hantaviruses and shared a most recent common ancestor with the Asian hantaviruses Xuan Son and Laibin. Breakdown of the virus load in a bat animal showed that MAKV resembles rodent-borne hantaviruses in its organ distribution in that it predominantly occurred in the spleen and kidney; this provides a first insight into the infection pattern of bat-borne hantaviruses. Ancestral state reconstruction based on a tree of L gene sequences of all relevant hantavirus lineages was combined with phylogenetic fossil host hypothesis testing, leading to a statistically significant rejection of the mammalian superorder Euarchontoglires (including rodents) but not the superorder Laurasiatheria (including shrews, moles, and bats) as potential hosts of ancestral hantaviruses at most basal tree nodes. Our data supports the emerging concept of bats as previously overlooked hantavirus reservoir hosts. (C) 2016 Elsevier B.V. All rights reserved

Blimp-1 induces and Hobit maintains the cytotoxic mediator granzyme B in CD8 T cells

CD8 T cells acquire cytotoxic molecules including granzyme B during effector differentiation. Both tissue-resident memory CD8 T cells (Trm) and circulating CD45RA+ effector-type T cells (Temra) cells have the ability to retain granzyme B protein expression into the memory phase, but it is unclear how this persistence of cytolytic activity is regulated during steady state. Previously, we have described that the transcriptional regulators Hobit and Blimp-1 have overlapping target genes that include granzyme B, but their impact on the regulation of cytotoxicity in Trm and Temra cells during homeostasis has remained unclear. We examined the expression regulation of Hobit and Blimp-1 in murine and human CD8 T-cells to determine their timeframe of activity. While Blimp-1 mRNA was expressed throughout effector and memory T cells, Blimp-1 protein, was only transiently expressed during the effector stage. In contrast, Hobit mRNA and protein expression was stably maintained during quiescence, but downregulated after activation. Notably, Blimp-1 was required for expression of granzyme B in murine effector T cells and Trm, while Hobit specifically regulated granzyme B in murine Trm during the memory phase. These findings suggest that Blimp-1 initiates cytotoxic effector function and that Hobit maintains cytotoxicity in a deployment-ready modus in Trm