PLoS Biology最新文献

Mycobacterium tuberculosis (Mtb) releases the unusual terpene nucleoside 1-tuberculosinyladenosine (1-TbAd) to block lysosomal function and promote survival in human macrophages. Using conventional approaches, we found that genes Rv3377c and Rv3378c, but not Rv3376, were necessary for 1-TbAd biosynthesis. Here, we introduce linear models for mass spectrometry (limms) software as a next-generation lipidomics tool to study the essential functions of lipid biosynthetic enzymes on a whole-cell basis. Using limms, whole-cell lipid profiles deepened the phenotypic landscape of comparative mass spectrometry experiments and identified a large family of approximately 100 terpene nucleoside metabolites downstream of Rv3378c. We validated the identity of previously unknown adenine-, adenosine-, and lipid-modified tuberculosinol-containing molecules using synthetic chemistry and collisional mass spectrometry, including comprehensive profiling of bacterial lipids that fragment to adenine. We tracked terpene nucleoside genotypes and lipid phenotypes among Mycobacterium tuberculosis complex (MTC) species that did or did not evolve to productively infect either human or nonhuman mammals. Although 1-TbAd biosynthesis genes were thought to be restricted to the MTC, we identified the locus in unexpected species outside the MTC. Sequence analysis of the locus showed nucleotide usage characteristic of plasmids from plant-associated bacteria, clarifying the origin and timing of horizontal gene transfer to a pre-MTC progenitor. The data demonstrated correlation between high level terpene nucleoside biosynthesis and mycobacterial competence for human infection, and 2 mechanisms of 1-TbAd biosynthesis loss. Overall, the selective gain and evolutionary retention of tuberculosinyl metabolites in modern species that cause human TB suggest a role in human TB disease, and the newly discovered molecules represent candidate disease-specific biomarkers.

The nonsense-mediated mRNA decay (NMD) pathway clears eukaryotic cells of mRNAs containing premature termination codons (PTCs) or normal stop codons located in specific contexts. It therefore plays an important role in gene expression regulation. The precise molecular mechanism of the NMD pathway has long been considered to differ substantially from yeast to metazoa, despite the involvement of universally conserved factors such as the central ATP-dependent RNA-helicase Upf1. Here, we describe the crystal structure of the yeast Upf1 bound to its recently identified but yet uncharacterized partner Nmd4, show that Nmd4 stimulates Upf1 ATPase activity and that this interaction contributes to the elimination of NMD substrates. We also demonstrate that a region of Nmd4 critical for the interaction with Upf1 in yeast is conserved in the metazoan SMG6 protein, another major NMD factor. We show that this conserved region is involved in the interaction of SMG6 with UPF1 and that mutations in this region affect the levels of endogenous human NMD substrates. Our results support the universal conservation of the NMD mechanism in eukaryotes.

New mutations provide the source of all genetic variation but their impact on trait variation remains poorly understood. A new study published in PLOS Biology addresses this question, finding that new mutations exert only weak effects on some traits in mice.

Transport proteins play a crucial role in cellular metabolism and are central to many aspects of molecular biology and medicine. Determining the function of transport proteins experimentally is challenging, as they become unstable when isolated from cell membranes. Machine learning-based predictions could provide an efficient alternative. However, existing methods are limited to predicting a small number of specific substrates or broad transporter classes. These limitations stem partly from using small data sets for model training and a choice of input features that lack sufficient information about the prediction problem. Here, we present SPOT, the first general machine learning model that can successfully predict specific substrates for arbitrary transport proteins, achieving an accuracy above 92% on independent and diverse test data covering widely different transporters and a broad range of metabolites. SPOT uses Transformer Networks to represent transporters and substrates numerically. To overcome the problem of missing negative data for training, it augments a large data set of known transporter-substrate pairs with carefully sampled random molecules as non-substrates. SPOT not only predicts specific transporter-substrate pairs, but also outperforms previously published models designed to predict broad substrate classes for individual transport proteins. We provide a web server and Python function that allows users to explore the substrate scope of arbitrary transporters.

Understanding perturbations in circulating lipid levels that often occur years or decades before clinical symptoms may enhance our understanding of disease mechanisms and provide novel intervention opportunities. Here, we assessed if polygenic scores (PGSs) for complex traits could detect lipid dysfunctions related to the traits and provide new biological insights. We constructed genome-wide PGSs (approximately 1 million genetic variants) for 50 complex traits in 7,169 Finnish individuals with routine clinical lipid profiles and lipidomics measurements (179 lipid species). We identified 678 associations (P < 9.0 × 10-5) involving 26 traits and 142 lipids. Most of these associations were also validated with the actual phenotype measurements where available (89.5% of 181 associations where the trait was available), suggesting that these associations represent early signs of physiological changes of the traits. We detected many known relationships (e.g., PGS for body mass index (BMI) and lysophospholipids, PGS for type 2 diabetes and triacyglycerols) and those that suggested potential target for prevention strategies (e.g., PGS for venous thromboembolism and arachidonic acid). We also found association of PGS for favorable adiposity with increased sphingomyelins levels, suggesting a probable role of sphingomyelins in increased risk for certain disease, e.g., venous thromboembolism as reported previously, in favorable adiposity despite its favorable metabolic effect. Altogether, our study provides a comprehensive characterization of lipidomic alterations in genetic predisposition for a wide range of complex traits. The study also demonstrates potential of PGSs for complex traits to capture early, presymptomatic lipid alterations, highlighting its utility in understanding disease mechanisms and early disease detection.

Each generation, spontaneous mutations introduce heritable changes that tend to reduce fitness in populations of highly adapted living organisms. This erosion of fitness is countered by natural selection, which keeps deleterious mutations at low frequencies and ultimately removes most of them from the population. The classical way of studying the impact of spontaneous mutations is via mutation accumulation (MA) experiments, where lines of small effective population size are bred for many generations in conditions where natural selection is largely removed. Such experiments in microbes, invertebrates, and plants have generally demonstrated that fitness decays as a result of MA. However, the phenotypic consequences of MA in vertebrates are largely unknown, because no replicated MA experiment has previously been carried out. This gap in our knowledge is relevant for human populations, where societal changes have reduced the strength of natural selection, potentially allowing deleterious mutations to accumulate. Here, we study the impact of spontaneous MA on the mean and genetic variation for quantitative and fitness-related traits in the house mouse using the MA experimental design, with a cryopreserved control to account for environmental influences. We show that variation for morphological and life history traits accumulates at a sufficiently high rate to maintain genetic variation and selection response. Weight and tail length measures decrease significantly between 0.04% and 0.3% per generation with narrow confidence intervals. Fitness proxy measures (litter size and surviving offspring) decrease on average by about 0.2% per generation, but with confidence intervals overlapping zero. When extrapolated to humans, our results imply that the rate of fitness loss should not be of concern in the foreseeable future.

The role of dopamine in reward expectancy has led to the hypothesis that it is crucial for forming treatment expectations and placebo effects. However, a new study in PLOS Biology presents robust evidence against the causal role of dopamine in these processes.

Clathrin-mediated endocytosis (CME) is a critical trafficking process that begins when an elaborate endocytic protein network is established at the plasma membrane. Interaction of early endocytic proteins with anionic phospholipids and/or cargo has been suggested to trigger CME initiation. However, the exact mechanism by which CME sites are initiated has not been fully elucidated. In the budding yeast Saccharomyces cerevisiae, higher levels of anionic phospholipids and cargo molecules exist in the newly formed daughter cell compared to the levels in the mother cell during polarized growth. Taking advantage of this asymmetry, we quantitatively compared CME proteins in S. cerevisiae mother versus daughter cells, observing differences in the dynamics and composition of key endocytic proteins. Our results show that CME site initiation occurs preferentially on regions of the plasma membrane with a relatively higher density of endocytic cargo and/or acidic phospholipids. Furthermore, our combined live cell-imaging and yeast genetics analysis provided evidence for a molecular mechanism in which CME sites are initiated when Yap1801 and Yap1802 (yeast CALM/AP180) and Syp1 (yeast FCHo1/2) coordinate with anionic phospholipids and cargo molecules to trigger Ede1 (yeast Eps15)-centric CME initiation complex assembly at the plasma membrane.

The Wnt/β-catenin signaling pathway plays numerous essential roles in animal development and tissue/stem cell maintenance. The activation of genes regulated by Wnt/β-catenin signaling requires the nuclear accumulation of β-catenin, a transcriptional co-activator. β-catenin is recruited to many Wnt-regulated enhancers through direct binding to T-cell factor/lymphoid enhancer factor (TCF/LEF) family transcription factors. β-catenin has previously been reported to form phase-separated biomolecular condensates (BMCs), which was implicated as a component of β-catenin's mechanism of action. This function required aromatic amino acid residues in the intrinsically disordered regions (IDRs) at the N- and C-termini of the protein. In this report, we further explore a role for β-catenin BMCs in Wnt target gene regulation. We find that β-catenin BMCs are miscible with LEF1 BMCs in vitro and in cultured cells. We characterized a panel of β-catenin mutants with different combinations of aromatic residue mutations in human cell culture and Drosophila melanogaster. Our data support a model in which aromatic residues across both IDRs contribute to BMC formation and signaling activity. Although different Wnt targets have different sensitivities to loss of β-catenin's aromatic residues, the activation of every target examined was compromised by aromatic substitution. These mutants are not defective in nuclear import or co-immunoprecipitation with several β-catenin binding partners. In addition, residues in the N-terminal IDR with no previously known role in signaling are clearly required for the activation of various Wnt readouts. Consistent with this, deletion of the N-terminal IDR results in a loss of signaling activity, which can be rescued by the addition of heterologous IDRs enriched in aromatic residues. Overall, our work supports a model in which the ability of β-catenin to form biomolecular condensates in the nucleus is tightly linked to its function as a transcriptional co-regulator.

Interferons (IFNs) play a crucial role in the regulation and evolution of host-virus interactions. Here, we conducted a genome-wide arrayed CRISPR knockout screen in the presence and absence of IFN to identify human genes that influence Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. We then performed an integrated analysis of genes interacting with SARS-CoV-2, drawing from a selection of 67 large-scale studies, including our own. We identified 28 genes of high relevance in both human genetic studies of Coronavirus Disease 2019 (COVID-19) patients and functional genetic screens in cell culture, with many related to the IFN pathway. Among these was the IFN-stimulated gene PLSCR1. PLSCR1 did not require IFN induction to restrict SARS-CoV-2 and did not contribute to IFN signaling. Instead, PLSCR1 specifically restricted spike-mediated SARS-CoV-2 entry. The PLSCR1-mediated restriction was alleviated by TMPRSS2 overexpression, suggesting that PLSCR1 primarily restricts the endocytic entry route. In addition, recent SARS-CoV-2 variants have adapted to circumvent the PLSCR1 barrier via currently undetermined mechanisms. Finally, we investigate the functional effects of PLSCR1 variants present in humans and discuss an association between PLSCR1 and severe COVID-19 reported recently.