Discovery of antimicrobial peptides in the global microbiome with machine learning.

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic.

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Global epistasis and the emergence of function in microbial consortia.

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

Transcription-Coupled Nucleotide Excision Repair and the Transcriptional Response to UV-Induced DNA Damage.

Ultraviolet (UV) irradiation and other genotoxic stresses induce bulky DNA lesions, which threaten genome stability and cell viability. Cells have evolved two main repair pathways to remove such lesions: global genome nucleotide excision repair (GG-NER) and transcription-coupled nucleotide excision repair (TC-NER). The modes by which these subpathways recognize DNA lesions are distinct, but they converge onto the same downstream steps for DNA repair. Here, we first summarize the current understanding of these repair mechanisms, specifically focusing on the roles of stalled RNA polymerase II, Cockayne syndrome protein B (CSB), CSA and UV-stimulated scaffold protein A (UVSSA) in TC-NER. We also discuss the intriguing role of protein ubiquitylation in this process. Additionally, we highlight key aspects of the effect of UV irradiation on transcription and describe the role of signaling cascades in orchestrating this response. Finally, we describe the pathogenic mechanisms underlying xeroderma pigmentosum and Cockayne syndrome, the two main diseases linked to mutations in NER factors.

Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern.

The Alpha, Beta, and Gamma SARS-CoV-2 variants of concern (VOCs) co-circulated globally during 2020 and 2021, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, which, in turn, was displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC and identify countries that acted as global and regional hubs of dissemination. We demonstrate the declining role of presumed origin countries of VOCs in their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1%-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of its emergence, associated with accelerated passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants, with implications for genomic surveillance along the hierarchical airline network.

Adaptive evolution of the enigmatic Takakia now facing climate change in Tibet.

The most extreme environments are the most vulnerable to transformation under a rapidly changing climate. These ecosystems harbor some of the most specialized species, which will likely suffer the highest extinction rates. We document the steepest temperature increase (2010-2021) on record at altitudes of above 4,000 m, triggering a decline of the relictual and highly adapted moss Takakia lepidozioides. Its de-novo-sequenced genome with 27,467 protein-coding genes includes distinct adaptations to abiotic stresses and comprises the largest number of fast-evolving genes under positive selection. The uplift of the study site in the last 65 million years has resulted in life-threatening UV-B radiation and drastically reduced temperatures, and we detected several of the molecular adaptations of Takakia to these environmental changes. Surprisingly, specific morphological features likely occurred earlier than 165 mya in much warmer environments. Following nearly 400 million years of evolution and resilience, this species is now facing extinction.

A global metagenomic map of urban microbiomes and antimicrobial resistance.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome.

Ocean microbial communities strongly influence the biogeochemistry, food webs, and climate of our planet. Despite recent advances in understanding their taxonomic and genomic compositions, little is known about how their transcriptomes vary globally. Here, we present a dataset of 187 metatranscriptomes and 370 metagenomes from 126 globally distributed sampling stations and establish a resource of 47 million genes to study community-level transcriptomes across depth layers from pole-to-pole. We examine gene expression changes and community turnover as the underlying mechanisms shaping community transcriptomes along these axes of environmental variation and show how their individual contributions differ for multiple biogeochemically relevant processes. Furthermore, we find the relative contribution of gene expression changes to be significantly lower in polar than in non-polar waters and hypothesize that in polar regions, alterations in community activity in response to ocean warming will be driven more strongly by changes in organismal composition than by gene regulatory mechanisms. VIDEO ABSTRACT.

Deep mutational scanning reveals functional constraints and antibody-escape potential of Lassa virus glycoprotein complex.

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of the Lassa virus's glycoprotein complex (GPC), which mediates viral entry into cells and is the target of neutralizing antibodies. To map the evolutionary space accessible to GPC, we used pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affected cell entry and antibody neutralization. Our experiments defined functional constraints throughout GPC. We quantified how GPC mutations affected neutralization with a panel of monoclonal antibodies. All antibodies tested were escaped by mutations that existed among natural Lassa virus lineages. Overall, our work describes a biosafety-level-2 method to elucidate the mutational space accessible to GPC and shows how prospective characterization of antigenic variation could aid the design of therapeutics and vaccines.

The Eukaryotic Proteome Is Shaped by E3 Ubiquitin Ligases Targeting C-Terminal Degrons.

Degrons are minimal elements that mediate the interaction of proteins with degradation machineries to promote proteolysis. Despite their central role in proteostasis, the number of known degrons remains small, and a facile technology to characterize them is lacking. Using a strategy combining global protein stability (GPS) profiling with a synthetic human peptidome, we identify thousands of peptides containing degron activity. Employing CRISPR screening, we establish that the stability of many proteins is regulated through degrons located at their C terminus. We characterize eight Cullin-RING E3 ubiquitin ligase (CRL) complex adaptors that regulate C-terminal degrons, including six CRL2 and two CRL4 complexes, and computationally implicate multiple non-CRLs in end recognition. Proteome analysis revealed that the C termini of eukaryotic proteins are depleted for C-terminal degrons, suggesting an E3-ligase-dependent modulation of proteome composition. Thus, we propose that a series of "C-end rules" operate to govern protein stability and shape the eukaryotic proteome.

Ubiquitin-independent proteasomal degradation driven by C-degron pathways.

Although most eukaryotic proteins are targeted for proteasomal degradation by ubiquitination, a subset have been demonstrated to undergo ubiquitin-independent proteasomal degradation (UbInPD). However, little is known about the molecular mechanisms driving UbInPD and the degrons involved. Utilizing the GPS-peptidome approach, a systematic method for degron discovery, we found thousands of sequences that promote UbInPD; thus, UbInPD is more prevalent than currently appreciated. Furthermore, mutagenesis experiments revealed specific C-terminal degrons required for UbInPD. Stability profiling of a genome-wide collection of human open reading frames identified 69 full-length proteins subject to UbInPD. These included REC8 and CDCA4, proteins which control proliferation and survival, as well as mislocalized secretory proteins, suggesting that UbInPD performs both regulatory and protein quality control functions. In the context of full-length proteins, C termini also play a role in promoting UbInPD. Finally, we found that Ubiquilin family proteins mediate the proteasomal targeting of a subset of UbInPD substrates.

Elucidation of E3 ubiquitin ligase specificity through proteome-wide internal degron mapping.

The ubiquitin-proteasome system plays a critical role in biology by regulating protein degradation. Despite their importance, precise recognition specificity is known for a few of the 600 E3s. Here, we establish a two-pronged strategy for identifying and mapping critical residues of internal degrons on a proteome-scale in HEK-293T cells. We employ global protein stability profiling combined with machine learning to identify 15,800 peptides likely to contain sequence-dependent degrons. We combine this with scanning mutagenesis to define critical residues for over 5,000 predicted degrons. Focusing on Cullin-RING ligase degrons, we generated mutational fingerprints for 219 degrons and developed DegronID, a computational algorithm enabling the clustering of degron peptides with similar motifs. CRISPR analysis enabled the discovery of E3-degron pairs, of which we uncovered 16 pairs that revealed extensive degron variability and structural determinants. We provide the visualization of these data on the public DegronID data browser as a resource for future exploration.

Theory of the Multiregional Neocortex: Large-Scale Neural Dynamics and Distributed Cognition.

The neocortex is a complex neurobiological system with many interacting regions. How these regions work together to subserve flexible behavior and cognition has become increasingly amenable to rigorous research. Here, I review recent experimental and theoretical work on the modus operandi of a multiregional cortex. These studies revealed several general principles for the neocortical interareal connectivity, low-dimensional macroscopic gradients of biological properties across cortical areas, and a hierarchy of timescales for information processing. Theoretical work suggests testable predictions regarding differential excitation and inhibition along feedforward and feedback pathways in the cortical hierarchy. Furthermore, modeling of distributed working memory and simple decision-making has given rise to a novel mathematical concept, dubbed bifurcation in space, that potentially explains how different cortical areas, with a canonical circuit organization but gradients of biological heterogeneities, are able to subserve their respective (e.g., sensory coding versus executive control) functions in a modularly organized brain.

Integrative oncology: Addressing the global challenges of cancer prevention and treatment.

The increase in cancer incidence and mortality is challenging current cancer care delivery globally, disproportionally affecting low- and middle-income countries (LMICs) when it comes to receiving evidence-based cancer prevention, treatment, and palliative and survivorship care. Patients in LMICs often rely on traditional, complementary, and integrative medicine (TCIM) that is more familiar, less costly, and widely available. However, spheres of influence and tensions between conventional medicine and TCIM can further disrupt efforts in evidence-based cancer care. Integrative oncology provides a framework to research and integrate safe, effective TCIM alongside conventional cancer treatment and can help bridge health care gaps in delivering evidence-informed, patient-centered care. This growing field uses lifestyle modifications, mind and body therapies (eg, acupuncture, massage, meditation, and yoga), and natural products to improve symptom management and quality of life among patients with cancer. On the basis of this review of the global challenges of cancer control and the current status of integrative oncology, the authors recommend: 1) educating and integrating TCIM providers into the cancer control workforce to promote risk reduction and culturally salient healthy life styles; 2) developing and testing TCIM interventions to address cancer symptoms or treatment-related adverse effects (eg, pain, insomnia, fatigue); and 3) disseminating and implementing evidence-based TCIM interventions as part of comprehensive palliative and survivorship care so patients from all cultures can live with or beyond cancer with respect, dignity, and vitality. With conventional medicine and TCIM united under a cohesive framework, integrative oncology may provide citizens of the world with access to safe, effective, evidence-informed, and culturally sensitive cancer care.

Versatility and Complexity: Common and Uncommon Facets of LysR-Type Transcriptional Regulators.

LysR-type transcriptional regulators (LTTRs) form one of the largest families of bacterial regulators. They are widely distributed and contribute to all aspects of metabolism and physiology. Most are homotetramers, with each subunit composed of an N-terminal DNA-binding domain followed by a long helix connecting to an effector-binding domain. LTTRs typically bind DNA in the presence or absence of a small-molecule ligand (effector). In response to cellular signals, conformational changes alter DNA interactions, contact with RNA polymerase, and sometimes contact with other proteins. Many are dual-function repressor-activators, although different modes of regulation may occur at multiple promoters. This review presents an update on the molecular basis of regulation, the complexity of regulatory schemes, and applications in biotechnology and medicine. The abundance of LTTRs reflects their versatility and importance. While a single regulatory model cannot describe all family members, a comparison of similarities and differences provides a framework for future study.

A Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis.

The aim of fine mapping is to identify genetic variants causally contributing to complex traits or diseases. Existing fine-mapping methods employ Bayesian discrete mixture priors and depend on a pre-specified maximum number of causal variants, which may lead to sub-optimal solutions. In this work, we propose a Bayesian fine-mapping method called h2-D2, utilizing a continuous global-local shrinkage prior. We also present an approach to define credible sets of causal variants in continuous prior settings. Simulation studies demonstrate that h2-D2 outperforms current state-of-the-art fine-mapping methods such as SuSiE and FINEMAP in accurately identifying causal variants and estimating their effect sizes. We further applied h2-D2 to prostate cancer analysis and discovered some previously unknown causal variants. In addition, we inferred 369 target genes associated with the detected causal variants and several pathways that were significantly over-represented by these genes, shedding light on their potential roles in prostate cancer development and progression.

Mono-allelic KCNB2 variants lead to a neurodevelopmental syndrome caused by altered channel inactivation.

Ion channels mediate voltage fluxes or action potentials that are central to the functioning of excitable cells such as neurons. The KCNB family of voltage-gated potassium channels (Kv) consists of two members (KCNB1 and KCNB2) encoded by KCNB1 and KCNB2, respectively. These channels are major contributors to delayed rectifier potassium currents arising from the neuronal soma which modulate overall excitability of neurons. In this study, we identified several mono-allelic pathogenic missense variants in KCNB2, in individuals with a neurodevelopmental syndrome with epilepsy and autism in some individuals. Recurrent dysmorphisms included a broad forehead, synophrys, and digital anomalies. Additionally, we selected three variants where genetic transmission has not been assessed, from two epilepsy studies, for inclusion in our experiments. We characterized channel properties of these variants by expressing them in oocytes of Xenopus laevis and conducting cut-open oocyte voltage clamp electrophysiology. Our datasets indicate no significant change in absolute conductance and conductance-voltage relationships of most disease variants as compared to wild type (WT), when expressed either alone or co-expressed with WT-KCNB2. However, variants c.1141A>G (p.Thr381Ala) and c.641C>T (p.Thr214Met) show complete abrogation of currents when expressed alone with the former exhibiting a left shift in activation midpoint when expressed alone or with WT-KCNB2. The variants we studied, nevertheless, show collective features of increased inactivation shifted to hyperpolarized potentials. We suggest that the effects of the variants on channel inactivation result in hyper-excitability of neurons, which contributes to disease manifestations.

Real-time emulation of future global warming reveals realistic impacts on the phenological response and quality deterioration in rice.

Decreased production of crops due to climate change has been predicted scientifically. While climate-resilient crops are necessary to ensure food security and support sustainable agriculture, predicting crop growth under future global warming is challenging. Therefore, we aimed to assess the impact of realistic global warming conditions on rice cultivation. We developed a crop evaluation platform, the agro-environment (AE) emulator, which generates diverse environments by implementing the complexity of natural environmental fluctuations in customized, fully artificial lighting growth chambers. We confirmed that the environmental responsiveness of rice obtained in the fluctuation of artificial environments is similar to those exhibited in natural environments by validating our AE emulator using publicly available meteorological data from multiple years at the same location and multiple locations in the same year. Based on the representative concentration pathway, real-time emulation of severe global warming unveiled dramatic advances in the rice life cycle, accompanied by a 35% decrease in grain yield and an 85% increase in quality deterioration, which is higher than the recently reported projections. The transcriptome dynamism showed that increasing temperature and CO2 concentrations synergistically changed the expression of various genes and strengthened the induction of flowering, heat stress adaptation, and CO2 response genes. The predicted severe global warming greatly alters rice environmental adaptability and negatively impacts rice production. Our findings offer innovative applications of artificial environments and insights for enhancing varietal potential and cultivation methods in the future.

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity.

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

The dawn of the tropical Atlantic invasion into the Mediterranean Sea.

The Mediterranean Sea is a marine biodiversity hotspot already affected by climate-driven biodiversity collapses. Its highly endemic fauna is at further risk if global warming triggers an invasion of tropical Atlantic species. Here, we combine modern species occurrences with a unique paleorecord from the Last Interglacial (135 to 116 ka), a conservative analog of future climate, to model the future distribution of an exemplary subset of tropical West African mollusks, currently separated from the Mediterranean by cold upwelling off north-west Africa. We show that, already under an intermediate climate scenario (RCP 4.5) by 2050, climatic connectivity along north-west Africa may allow tropical species to colonize a by then largely environmentally suitable Mediterranean. The worst-case scenario RCP 8.5 leads to a fully tropicalized Mediterranean by 2100. The tropical Atlantic invasion will add to the ongoing Indo-Pacific invasion through the Suez Canal, irreversibly transforming the entire Mediterranean into a novel ecosystem unprecedented in human history.