Ocean plankton comprise organisms from viruses to fish larvae that are fundamental to ecosystem functioning and the provision of marine services such as fisheries and CO sequestration. The latter services are partly governed by variations in plankton community composition and the expression of traits such as body size at community-level. While community assembly has been thoroughly studied for the smaller end of the plankton size spectrum, the larger end comprises ectotherms that are often studied at the species, or group-level, rather than as communities. The body size of marine ectotherms decreases with temperature, but controls on community-level traits remain elusive, hindering the predictability of marine services provision. Here, we leverage Tara Oceans datasets to determine how zooplankton community composition and size structure varies with latitude, temperature and productivity-related covariates in the global surface ocean. Zooplankton abundance and median size decreased towards warmer and less productive environments, as a result of changes in copepod composition. However, some clades displayed the opposite relationships, which may be ascribed to alternative feeding strategies. Given that climate models predict increasingly warmed and stratified oceans, our findings suggest that zooplankton communities will shift towards smaller organisms which might weaken their contribution to the biological carbon pump.

Inspired by recent proteomic data demonstrating the upregulation of carbon and glycogen metabolism in aging human hematopoietic stem and progenitor cells (HPCs, CD34+ cells), this report addresses whether this is caused by elevated glycolysis of the HPCs on a per cell basis, or by a subpopulation that has become more glycolytic. The average glycogen content in individual CD34+ cells from older subjects (> 50 years) was 3.5 times higher and more heterogeneous compared to younger subjects (< 35 years). Representative glycolytic enzyme activities in HPCs confirmed a significant increase in glycolysis in older subjects. The HPCs from older subjects can be fractionated into three distinct subsets with high, intermediate, and low glucose uptake (GU) capacity, while the subset with a high GU capacity could scarcely be detected in younger subjects. Thus, we conclude that upregulated glycolysis in aging HPCs is caused by the expansion of a more glycolytic HPC subset. Since single-cell RNA analysis has also demonstrated that this subpopulation is linked to myeloid differentiation and increased proliferation, isolation and mechanistic characterization of this subpopulation can be utilized to elucidate specific targets for therapeutic interventions to restore the lineage balance of aging HPCs.

Blowflies and houseflies are mechanical vectors inhabiting synanthropic environments around the world. They feed and breed in fecal and decaying organic matter, but the microbiome they harbour and transport is largely uncharacterized. We sampled 116 individual houseflies and blowflies from varying habitats on three continents and subjected them to high-coverage, whole-genome shotgun sequencing. This allowed for genomic and metagenomic analyses of the host-associated microbiome at the species level. Both fly host species segregate based on principal coordinate analysis of their microbial communities, but they also show an overlapping core microbiome. Legs and wings displayed the largest microbial diversity and were shown to be an important route for microbial dispersion. The environmental sequencing approach presented here detected a stochastic distribution of human pathogens, such as Helicobacter pylori, thereby demonstrating the potential of flies as proxies for environmental and public health surveillance.

Trichuris suis ova (TSO) have been tested for therapeutic application in inflammatory bowel diseases (IBD) yet understanding of the underlying mechanisms and safety in an immunocompromised host is limited due to lack of a suitable animal model. We used a recently established rabbit model of dextran sodium sulphate (DSS) induced colitis to study the efficacy, mechanisms and safety of TSO therapy in immunocompetent and immunosuppressed animals. TSO treatment prevented the DSS induced weight loss, delayed the onset of DSS induced symptoms by 2 days and significantly reduced the disease activity (DAI). TSO treatment protected caecal histology and prevented the colitis-associated loss in faecal microbiota diversity. Mainly the transcriptome of lamina propria mononuclear cells (LPMC) was affected by TSO treatment, showing dampened innate and adaptive inflammatory responses. The protective effect of TSO was lost in immunosuppressed rabbits, where TSO exacerbated colitis. Our data show that preventive TSO treatment ameliorates colitis severity in immunocompetent rabbits, modulates LPMC immune responses and reduces faecal dysbiosis. In contrast, the same TSO treatment exacerbates colitis in immunosuppressed animals. Our data provide further evidence for a therapeutic effect of TSO in IBD, yet caution is required with regard to TSO treatment in immunosuppressed patients.

Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http://gear.comp-sysbio.org.

Phosphorylation and proteolysis are among the most common post-translational modifications (PTMs), and play critical roles in various biological processes. More recent discoveries imply that the crosstalks between these two PTMs are involved in many diseases. In this work, we construct a post-translational regulatory network (PTRN) consists of phosphorylation and proteolysis processes, which enables us to investigate the regulatory interplays between these two PTMs. With the PTRN, we identify some functional network motifs that are significantly enriched with drug targets, some of which are further found to contain multiple proteins targeted by combinatorial drugs. These findings imply that the network motifs may be used to predict targets when designing new drugs. Inspired by this, we propose a novel computational approach called NetTar for predicting drug targets using the identified network motifs. Benchmarking results on real data indicate that our approach can be used for accurate prediction of novel proteins targeted by known drugs.