HIV‐1 infection of CD4 T cells impairs antigen‐specific B cell function

Failures to produce neutralizing antibodies upon HIV‐1 infection result in part from B‐cell dysfunction due to unspecific B‐cell activation. How HIV‐1 affects antigen‐specific B‐cell functions remains elusive. Using an adoptive transfer mouse model and ex vivo HIV infection of human tonsil tissue, we found that expression of the HIV‐1 pathogenesis factor NEF in CD4 T cells undermines their helper function and impairs cognate B‐cell functions including mounting of efficient specific IgG responses. NEF interfered with T cell help via a specific protein interaction motif that prevents polarized cytokine secretion at the T‐cell–B‐cell immune synapse. This interference reduced B‐cell activation and proliferation and thus disrupted germinal center formation and affinity maturation. These results identify NEF as a key component for HIV‐mediated dysfunction of antigen‐specific B cells. Therapeutic targeting of the identified molecular surface in NEF will facilitate host control of HIV infection.     

CellRegMap: a statistical framework for mapping context‐specific regulatory variants using scRNA‐seq

Single‐cell RNA sequencing (scRNA‐seq) enables characterizing the cellular heterogeneity in human tissues. Recent technological advances have enabled the first population‐scale scRNA‐seq studies in hundreds of individuals, allowing to assay genetic effects with single‐cell resolution. However, existing strategies to analyze these data remain based on principles established for the genetic analysis of bulk RNA‐seq. In particular, current methods depend on a priori definitions of discrete cell types, and hence cannot assess allelic effects across subtle cell types and cell states. To address this, we propose the Cell Regulatory Map (CellRegMap), a statistical framework to test for and quantify genetic effects on gene expression in individual cells. CellRegMap provides a principled approach to identify and characterize genotype–context interactions of known eQTL variants using scRNA‐seq data. This model‐based approach resolves allelic effects across cellular contexts of different granularity, including genetic effects specific to cell subtypes and continuous cell transitions. We validate CellRegMap using simulated data and apply it to previously identified eQTL from two recent studies of differentiating iPSCs, where we uncover hundreds of eQTL displaying heterogeneity of genetic effects across cellular contexts. Finally, we identify fine‐grained genetic regulation in neuronal subtypes for eQTL that are colocalized with human disease variants.     

Multi‐modal meta‐analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor

Molecular and functional profiling of cancer cell lines is subject to laboratory‐specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta‐analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi‐modal meta‐analysis approach also identified synthetic lethal partners of cancer drivers, including a co‐dependency of PTEN deficient endometrial cancer cells on RNA helicases.     

SARS‐CoV‐2 infection remodels the host protein thermal stability landscape

The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a global threat to human health and has compromised economic stability. In addition to the development of an effective vaccine, it is imperative to understand how SARS‐CoV‐2 hijacks host cellular machineries on a system‐wide scale so that potential host‐directed therapies can be developed. In situ proteome‐wide abundance and thermal stability measurements using thermal proteome profiling (TPP) can inform on global changes in protein activity. Here we adapted TPP to high biosafety conditions amenable to SARS‐CoV‐2 handling. We discovered pronounced temporal alterations in host protein thermostability during infection, which converged on cellular processes including cell cycle, microtubule and RNA splicing regulation. Pharmacological inhibition of host proteins displaying altered thermal stability or abundance during infection suppressed SARS‐CoV‐2 replication. Overall, this work serves as a framework for expanding TPP workflows to globally important human pathogens that require high biosafety containment and provides deeper resolution into the molecular changes induced by SARS‐CoV‐2 infection.     

Degrees of compositional shift in tree communities vary along a gradient of temperature change rates over one decade: Application of an individual‐based temporal beta‐diversity concept

Temporal patterns in communities have gained widespread attention recently, to the extent that temporal changes in community composition are now termed “temporal beta‐diversity.” Previous studies of beta‐diversity have made use of two classes of dissimilarity indices: incidence‐based (e.g., Sørensen and Jaccard dissimilarity) and abundance‐based (e.g., Bray–Curtis and Ružička dissimilarity). However, in the context of temporal beta‐diversity, the persistence of identical individuals and turnover among other individuals within the same species over time have not been considered, despite the fact that both will affect compositional changes in communities. To address this issue, I propose new index concepts for beta‐diversity and the relative speed of compositional shifts in relation to individual turnover based on individual identity information. Individual‐based beta‐diversity indices are novel dissimilarity indices that consider individual identity information to quantitatively evaluate temporal change in individual turnover and community composition. I applied these new indices to individually tracked tree monitoring data in deciduous and evergreen broad‐leaved forests across the Japanese archipelago with the objective of quantifying the effect of climate change trends (i.e., rates of change in both annual mean temperature and annual precipitation) on individual turnover and compositional shifts at each site. A new index explored the relative contributions of mortality and recruitment processes to temporal changes in community composition. Clear patterns emerged showing that an increase in the temperature change rate facilitated the relative contribution of mortality components. The relative speed of compositional shift increased with increasing temperature change rates in deciduous forests but decreased with increasing warming rates in evergreen forests. These new concepts provide a way to identify novel and high‐resolution temporal patterns in communities.     

Non‐invasive monitoring of multiple wildlife health factors by fecal microbiome analysis

Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body‐fat). We paired a feature‐selection algorithm with an LDA‐classifier trained on elk differential bacterial abundance (16S‐rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave‐one‐out cross‐validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body‐fat, sex, and age‐class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non‐invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome‐based monitoring of wildlife populations and supports hypothetical expectations found in host‐microbiome theory.     

Predictable fold switching by the SARS‐CoV‐2 protein ORF9b

Extant fold‐switching proteins remodel their secondary structures and change their functions in response to environmental stimuli. These shapeshifting proteins regulate biological processes and are associated with a number of diseases, including tuberculosis, cancer, Alzheimer''s, and autoimmune disorders. Thus, predictive methods are needed to identify more fold‐switching proteins, especially since all naturally occurring instances have been discovered by chance. In response to this need, two high‐throughput predictive methods have recently been developed. Here we test them on ORF9b, a newly discovered fold switcher and potential therapeutic target from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2). Promisingly, both methods correctly indicate that ORF9b switches folds. We then tested the same two methods on ORF9b1, the ORF9b homolog from SARS‐CoV‐1. Again, both methods predict that ORF9b1 switches folds, a finding consistent with experimental binding studies. Together, these results (a) demonstrate that protein fold switching can be predicted using high‐throughput computational approaches and (b) suggest that fold switching might be a general characteristic of ORF9b homologs.     

Aging‐related cell type‐specific pathophysiologic immune responses that exacerbate disease severity in aged COVID‐19 patients

Coronavirus disease 2019 (COVID‐19) is especially severe in aged patients, defined as 65 years or older, for reasons that are currently unknown. To investigate the underlying basis for this vulnerability, we performed multimodal data analyses on immunity, inflammation, and COVID‐19 incidence and severity as a function of age. Our analysis leveraged age‐specific COVID‐19 mortality and laboratory testing from a large COVID‐19 registry, along with epidemiological data of ~3.4 million individuals, large‐scale deep immune cell profiling data, and single‐cell RNA‐sequencing data from aged COVID‐19 patients across diverse populations. We found that decreased lymphocyte count and elevated inflammatory markers (C‐reactive protein, D‐dimer, and neutrophil–lymphocyte ratio) are significantly associated with age‐specific COVID‐19 severities. We identified the reduced abundance of naïve CD8 T cells with decreased expression of antiviral defense genes (i.e., IFITM3 and TRIM22) in aged severe COVID‐19 patients. Older individuals with severe COVID‐19 displayed type I and II interferon deficiencies, which is correlated with SARS‐CoV‐2 viral load. Elevated expression of SARS‐CoV‐2 entry factors and reduced expression of antiviral defense genes (LY6E and IFNAR1) in the secretory cells are associated with critical COVID‐19 in aged individuals. Mechanistically, we identified strong TGF‐beta‐mediated immune–epithelial cell interactions (i.e., secretory‐non‐resident macrophages) in aged individuals with critical COVID‐19. Taken together, our findings point to immuno‐inflammatory factors that could be targeted therapeutically to reduce morbidity and mortality in aged COVID‐19 patients.     

The free energy folding penalty accompanying binding of intrinsically disordered α‐helical motifs

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes and preform critical roles in many cellular processes, most often through the association with globular proteins. Despite lacking a stable three‐dimensional structure by themselves, they may acquire a defined conformation upon binding globular targets. The most common type of secondary structure acquired by these binding motifs entails formation of an α‐helix. It has been hypothesized that such disorder‐to‐order transitions are associated with a significant free energy penalty due to IDP folding, which reduces the overall IDP‐target affinity. However, the exact magnitude of IDP folding penalty in α‐helical binding motifs has not been systematically estimated. Here, we report the folding penalty contributions for 30 IDPs undergoing folding‐upon‐binding and find that the average IDP folding penalty is +2.0 kcal/mol and ranges from 0.7 to 3.5 kcal/mol. We observe that the folding penalty scales approximately linearly with the change in IDP helicity upon binding, which provides a simple empirical way to estimate folding penalty. We analyze to what extent do pre‐structuring and target‐bound IDP dynamics (fuzziness) reduce the folding penalty and find that these effects combined, on average, reduce the folding cost by around half. Taken together, the presented analysis provides a quantitative basis for understanding the role of folding penalty in IDP‐target interactions and introduces a method estimate this quantity. Estimation and reduction of IDP folding penalty may prove useful in the rational design of helix‐stabilized inhibitors of IDP‐target interactions.StatementThe α‐helical binding motifs are ubiquitous among the intrinsically disordered proteins (IDPs). Upon binding their targets, they undergo a disorder‐to‐order transition, which is accompanied by a significant folding penalty whose magnitude is generally not known. Here, we use recently developed statistical‐thermodynamic model to estimate the folding penalties for 30 IDPs and clarify the roles of IDP pre‐folding and bound‐state dynamics in reducing the folding penalty.     

Molecular basis of cross‐species ACE2 interactions with SARS‐CoV‐2‐like viruses of pangolin origin

Pangolins have been suggested as potential reservoir of zoonotic viruses, including SARS‐CoV‐2 causing the global COVID‐19 outbreak. Here, we study the binding of two SARS‐CoV‐2‐like viruses isolated from pangolins, GX/P2V/2017 and GD/1/2019, to human angiotensin‐converting enzyme 2 (hACE2), the receptor of SARS‐CoV‐2. We find that the spike protein receptor‐binding domain (RBD) of pangolin CoVs binds to hACE2 as efficiently as the SARS‐CoV‐2 RBD in vitro. Furthermore, incorporation of pangolin CoV RBDs allows entry of pseudotyped VSV particles into hACE2‐expressing cells. A screen for binding of pangolin CoV RBDs to ACE2 orthologs from various species suggests a broader host range than that of SARS‐CoV‐2. Additionally, cryo‐EM structures of GX/P2V/2017 and GD/1/2019 RBDs in complex with hACE2 show their molecular binding in modes similar to SARS‐CoV‐2 RBD. Introducing the Q498H substitution found in pangolin CoVs into the SARS‐CoV‐2 RBD expands its binding capacity to ACE2 homologs of mouse, rat, and European hedgehog. These findings suggest that these two pangolin CoVs may infect humans, highlighting the necessity of further surveillance of pangolin CoVs.     

Identification of lectin receptors for conserved SARS‐CoV‐2 glycosylation sites

New SARS‐CoV‐2 variants are continuously emerging with critical implications for therapies or vaccinations. The 22 N‐glycan sites of Spike remain highly conserved among SARS‐CoV‐2 variants, opening an avenue for robust therapeutic intervention. Here we used a comprehensive library of mammalian carbohydrate‐binding proteins (lectins) to probe critical sugar residues on the full‐length trimeric Spike and the receptor binding domain (RBD) of SARS‐CoV‐2. Two lectins, Clec4g and CD209c, were identified to strongly bind to Spike. Clec4g and CD209c binding to Spike was dissected and visualized in real time and at single‐molecule resolution using atomic force microscopy. 3D modelling showed that both lectins can bind to a glycan within the RBD‐ACE2 interface and thus interferes with Spike binding to cell surfaces. Importantly, Clec4g and CD209c significantly reduced SARS‐CoV‐2 infections. These data report the first extensive map and 3D structural modelling of lectin‐Spike interactions and uncovers candidate receptors involved in Spike binding and SARS‐CoV‐2 infections. The capacity of CLEC4G and mCD209c lectins to block SARS‐CoV‐2 viral entry holds promise for pan‐variant therapeutic interventions.     

Concordant geographic and genetic structure revealed by genotyping‐by‐sequencing in a New Zealand marine isopod

Population genetic structure in the marine environment can be influenced by life‐history traits such as developmental mode (biphasic, with distinct adult and larval morphology, and direct development, in which larvae resemble adults) or habitat specificity, as well as geography and selection. Developmental mode is thought to significantly influence dispersal, with direct developers expected to have much lower dispersal potential. However, this prediction can be complicated by the presence of geophysical barriers to dispersal. In this study, we use a panel of 8,020 SNPs to investigate population structure and biogeography over multiple spatial scales for a direct‐developing species, the New Zealand endemic marine isopod Isocladus armatus. Because our sampling range is intersected by two well‐known biogeographic barriers (the East Cape and the Cook Strait), our study provides an opportunity to understand how such barriers influence dispersal in direct developers. On a small spatial scale (20 km), gene flow between locations is extremely high, suggestive of an island model of migration. However, over larger spatial scales (600 km), populations exhibit a clear pattern of isolation‐by‐distance. Our results indicate that I. armatus exhibits significant migration across the hypothesized barriers and suggest that large‐scale ocean currents associated with these locations do not present a barrier to dispersal. Interestingly, we find evidence of a north‐south population genetic break occurring between Māhia and Wellington. While no known geophysical barrier is apparent in this area, it coincides with the location of a proposed border between bioregions. Analysis of loci under selection revealed that both isolation‐by‐distance and adaption may be contributing to the degree of population structure we have observed here. We conclude that developmental life history largely predicts dispersal in the intertidal isopod I. armatus. However, localized biogeographic processes can disrupt this expectation, and this may explain the potential meta‐population detected in the Auckland region.     

Cryo‐EM structure of the CENP‐A nucleosome in complex with phosphorylated CENP‐C

The CENP‐A nucleosome is a key structure for kinetochore assembly. Once the CENP‐A nucleosome is established in the centromere, additional proteins recognize the CENP‐A nucleosome to form a kinetochore. CENP‐C and CENP‐N are CENP‐A binding proteins. We previously demonstrated that vertebrate CENP‐C binding to the CENP‐A nucleosome is regulated by CDK1‐mediated CENP‐C phosphorylation. However, it is still unknown how the phosphorylation of CENP‐C regulates its binding to CENP‐A. It is also not completely understood how and whether CENP‐C and CENP‐N act together on the CENP‐A nucleosome. Here, using cryo‐electron microscopy (cryo‐EM) in combination with biochemical approaches, we reveal a stable CENP‐A nucleosome‐binding mode of CENP‐C through unique regions. The chicken CENP‐C structure bound to the CENP‐A nucleosome is stabilized by an intramolecular link through the phosphorylated CENP‐C residue. The stable CENP‐A‐CENP‐C complex excludes CENP‐N from the CENP‐A nucleosome. These findings provide mechanistic insights into the dynamic kinetochore assembly regulated by CDK1‐mediated CENP‐C phosphorylation.     

Alpha‐fetoprotein accelerates the progression of hepatocellular carcinoma by promoting Bcl‐2 gene expression through an RA‐RAR signalling pathway

Previous studies have found that alpha‐fetoprotein (AFP) can promote the proliferation of hepatoma cells and accelerate the progression of hepatocellular carcinoma (HCC). However, the exact mechanism of action remains unclear. Recent bioinformatics studies have predicted the possible interaction between AFP and retinoic acid receptors (RARs). Thus, the purpose of this study was to investigate the molecular mechanism through which AFP promotes tumour cell proliferation by interfering with the RA‐RAR signal pathway. Our data indicated that AFP could significantly promote the proliferation and weaken ATRA‐induced apoptosis of hepatoma cells. Besides, cytoplasmic AFP interacts with RAR, disrupting its entrance into the nucleus, which in turn affects the expression of the Bcl‐2 gene. In addition, knockdown of AFP in HepG2 cells was synchronously associated with an incremental increase of RAR binding to DNA, as well as down‐regulation of Bcl‐2; the opposite effect was observed in AFP gene‐transfected HLE cells. Moreover, a similar effect of AFP was detected in tumour tissues with high serum AFP, but not in adjacent non‐cancerous liver tissues, or HCC tissues with low serum AFP levels. These results indicate that AFP acts as signalling molecule and prevents RAR from entering into the nucleus by interacting with RAR, thereby promoting the expression of Bcl‐2. Our data reveal a novel mechanism through which AFP regulates Bcl‐2 expression and further suggest that AFP may be used as a novel target for treating HCC.     

The leucine zipper EF‐hand containing transmembrane protein‐1 EF‐hand is a tripartite calcium,temperature, and pH sensor

Leucine Zipper EF‐hand containing transmembrane protein‐1 (LETM1) is an inner mitochondrial membrane protein that mediates mitochondrial calcium (Ca²⁺)/proton exchange. The matrix residing carboxyl (C)‐terminal domain contains a sequence identifiable EF‐hand motif (EF1) that is highly conserved among orthologues. Deletion of EF1 abrogates LETM1 mediated mitochondrial Ca²⁺ flux, highlighting the requirement of EF1 for LETM1 function. To understand the mechanistic role of this EF‐hand in LETM1 function, we characterized the biophysical properties of EF1 in isolation. Our data show that EF1 exhibits α‐helical secondary structure that is augmented in the presence of Ca²⁺. Unexpectedly, EF1 features a weak (~mM), but specific, apparent Ca²⁺‐binding affinity, consistent with the canonical Ca²⁺ coordination geometry, suggested by our solution NMR. The low affinity is, at least in part, due to an Asp at position 12 of the binding loop, where mutation to Glu increases the affinity by ~4‐fold. Further, the binding affinity is sensitive to pH changes within the physiological range experienced by mitochondria. Remarkably, EF1 unfolds at high and low temperatures. Despite these unique EF‐hand properties, Ca²⁺ binding increases the exposure of hydrophobic regions, typical of EF‐hands; however, this Ca²⁺‐induced conformational change shifts EF1 from a monomer to higher order oligomers. Finally, we showed that a second, putative EF‐hand within LETM1 is unreactive to Ca²⁺ either in isolation or tandem with EF1. Collectively, our data reveal that EF1 is structurally and biophysically responsive to pH, Ca²⁺ and temperature, suggesting a role as a multipartite environmental sensor within LETM1.     

Is the grass always greener? Land surface phenology reveals differences in peak and season‐long vegetation productivity responses to climate and management

Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual‐resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season‐long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season‐long productivity. Annual precipitation and temperature had strong explanatory power for productivity‐related phenology measures but predicted date‐based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing‐season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land‐use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.     

Engineering defensin α‐helix to produce high‐affinity SARS‐CoV‐2 spike protein binding ligands

The binding of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) spike protein to the angiotensin‐converting enzyme 2 (ACE2) receptor expressed on the host cells is a critical initial step for viral infection. This interaction is blocked through competitive inhibition by soluble ACE2 protein. Therefore, developing high‐affinity and cost‐effective ACE2 mimetic ligands that disrupt this protein–protein interaction is a promising strategy for viral diagnostics and therapy. We employed human and plant defensins, a class of small (2–5 kDa) and highly stable proteins containing solvent‐exposed alpha‐helix, conformationally constrained by two disulfide bonds. Therefore, we engineered the amino acid residues on the constrained alpha‐helix of defensins to mimic the critical residues on the ACE2 helix 1 that interact with the SARS‐CoV‐2 spike protein. The engineered proteins (h‐deface2, p‐deface2, and p‐deface2‐MUT) were soluble and purified to homogeneity with a high yield from a bacterial expression system. The proteins demonstrated exceptional thermostability (Tm 70.7°C), high‐affinity binding to the spike protein with apparent K _d values of 54.4 ± 11.3, 33.5 ± 8.2, and 14.4 ± 3.5 nM for h‐deface2, p‐deface2, and p‐deface2‐MUT, respectively, and were used in a diagnostic assay that detected SARS‐CoV‐2 neutralizing antibodies. This work addresses the challenge of developing helical ACE2 mimetics by demonstrating that defensins provide promising scaffolds to engineer alpha‐helices in a constrained form for designing of high‐affinity ligands.