Cellular stress can globally inhibit translation initiation, and glucose removal from yeast causes one of the most dramatic effects in terms of rapidity and scale. Here we show that the same rapid inhibition occurs during yeast growth as glucose levels diminish. We characterize this novel regulation showing that it involves alterations within the 48S preinitiation complex. In particular, the interaction between eIF4A and eIF4G is destabilized, leading to a temporary stabilization of the eIF3-eIF4G interaction on the 48S complex. Under such conditions, specific mRNAs that are important for the adaptation to the new conditions must continue to be translated. We have determined which mRNAs remain translated early after glucose starvation. These experiments enable us to provide a physiological context for this translational regulation by ascribing defined functions that are translationally maintained or up-regulated. Overrepresented in this class of mRNA are those involved in carbohydrate metabolism, including several mRNAs from the pentose phosphate pathway. Our data support a hypothesis that a concerted preemptive activation of the pentose phosphate pathway, which targets both mRNA transcription and translation, is important for the transition from fermentative to respiratory growth in yeast.

The mechanisms by which RNA-binding proteins control the translation of subsets of mRNAs are not yet clear. Slf1p and Sro9p are atypical-La motif containing proteins which are members of a superfamily of RNA-binding proteins conserved in eukaryotes. RIP-Seq analysis of these two yeast proteins identified overlapping and distinct sets of mRNA targets, including highly translated mRNAs such as those encoding ribosomal proteins. In paralell, transcriptome analysis of slf1Δ and sro9Δ mutant strains indicated altered gene expression in similar functional classes of mRNAs following loss of each factor. The loss of SLF1 had a greater impact on the transcriptome, and in particular, revealed changes in genes involved in the oxidative stress response. slf1Δ cells are more sensitive to oxidants and RIP-Seq analysis of oxidatively stressed cells enriched Slf1p targets encoding antioxidants and other proteins required for oxidant tolerance. To quantify these effects at the protein level, we used label-free mass spectrometry to compare the proteomes of wild-type and slf1Δ strains following oxidative stress. This analysis identified several proteins which are normally induced in response to hydrogen peroxide, but where this increase is attenuated in the slf1Δ mutant. Importantly, a significant number of the mRNAs encoding these targets were also identified as Slf1p-mRNA targets. We show that Slf1p remains associated with the few translating ribosomes following hydrogen peroxide stress and that Slf1p co-immunoprecipitates ribosomes and members of the eIF4E/eIF4G/Pab1p 'closed loop' complex suggesting that Slf1p interacts with actively translated mRNAs following stress. Finally, mutational analysis of SLF1 revealed a novel ribosome interacting domain in Slf1p, independent of its RNA binding La-motif. Together, our results indicate that Slf1p mediates a translational response to oxidative stress via mRNA-specific translational control.

The transcriptional responses of yeast cells to diverse stresses typically include gene activation and repression. Specific stress defense, citric acid cycle and oxidative phosphorylation genes are activated, whereas protein synthesis genes are coordinately repressed. This view was achieved from comparative transcriptomic experiments delineating sets of genes whose expression greatly changed with specific stresses. Less attention has been paid to the biological significance of 1) consistent, albeit modest, changes in RNA levels across multiple conditions, and 2) the global gene expression correlations observed when comparing numerous genome-wide studies. To address this, we performed a meta-analysis of 1379 microarray-based experiments in yeast, and identified 1388 blocks of RNAs whose expression changes correlate across multiple and diverse conditions. Many of these blocks represent sets of functionally-related RNAs that act in a coordinated fashion under normal and stress conditions, and map to global cell defense and growth responses. Subsequently, we used the blocks to analyze novel RNA-seq experiments, demonstrating their utility and confirming the conclusions drawn from the meta-analysis. Our results provide a new framework for understanding the biological significance of changes in gene expression: 'archetypal' transcriptional blocks that are regulated in a concerted fashion in response to external stimuli.

Long-acting antiretroviral agents for preexposure prophylaxis (PrEP) represent a promising new alternative to daily oral regimens for HIV prevention. Lenacapavir (LEN) is a first-in-class long-acting capsid inhibitor approved for the treatment of HIV-1 infection. Here, we assessed the efficacy of LEN for PrEP using a single high-dose simian-human immunodeficiency virus (SHIV) rectal challenge macaque model. In vitro, LEN showed potent antiviral activity against SHIV, as it did for HIV-1. In macaques, a single subcutaneous administration of LEN demonstrated dose proportional increases in and durability of drug plasma levels. A high-dose SHIV inoculum for the PrEP efficacy evaluation was identified via virus titration in untreated macaques. LEN-treated macaques were challenged with high-dose SHIV 7 weeks after drug administration, and the majority remained protected from infection, as confirmed by plasma PCR, cell-associated proviral DNA, and serology testing. Complete protection and superiority to the untreated group was observed among animals whose LEN plasma exposure exceeded its model-adjusted clinical efficacy target at the time of challenge. All infected animals had subprotective LEN concentrations and showed no emergent resistance. These data demonstrate effective SHIV prophylaxis in a stringent macaque model at clinically relevant LEN exposures and support the clinical evaluation of LEN for HIV PrEP in humans.

Translation initiation factor eIF4E mediates mRNA selection for protein synthesis via the mRNA 5'cap. A family of binding proteins, termed the 4E-BPs, interact with eIF4E to hinder ribosome recruitment. Mechanisms underlying mRNA specificity for 4E-BP control remain poorly understood. Saccharomyces cerevisiae 4E-BPs, Caf20p and Eap1p, each regulate an overlapping set of mRNAs. We undertook global approaches to identify protein and RNA partners of both 4E-BPs by immunoprecipitation of tagged proteins combined with mass spectrometry or next-generation sequencing. Unexpectedly, mass spectrometry indicated that the 4E-BPs associate with many ribosomal proteins. 80S ribosome and polysome association was independently confirmed and was not dependent upon interaction with eIF4E, as mutated forms of both Caf20p and Eap1p with disrupted eIF4E-binding motifs retain ribosome interaction. Whole-cell proteomics revealed Caf20p mutations cause both up and down-regulation of proteins and that many changes were independent of the 4E-binding motif. Investigations into Caf20p mRNA targets by immunoprecipitation followed by RNA sequencing revealed a strong association between Caf20p and mRNAs involved in transcription and cell cycle processes, consistent with observed cell cycle phenotypes of mutant strains. A core set of over 500 Caf20p-interacting mRNAs comprised of both eIF4E-dependent (75%) and eIF4E-independent targets (25%), which differ in sequence attributes. eIF4E-independent mRNAs share a 3' UTR motif. Caf20p binds all tested motif-containing 3' UTRs. Caf20p and the 3'UTR combine to influence ERS1 mRNA polysome association consistent with Caf20p contributing to translational control. Finally ERS1 3'UTR confers Caf20-dependent repression of expression to a heterologous reporter gene. Taken together, these data reveal conserved features of eIF4E-dependent Caf20p mRNA targets and uncover a novel eIF4E-independent mode of Caf20p binding to mRNAs that extends the regulatory role of Caf20p in the mRNA-specific repression of protein synthesis beyond its interaction with eIF4E.

Single-cell gene expression is inherently variable, but how this variability is controlled in response to stimulation remains unclear. Here, we use single-cell RNA-seq and single-molecule mRNA counting (smFISH) to study inducible gene expression in the immune toll-like receptor system. We show that mRNA counts of tumor necrosis factor α conform to a standard stochastic switch model, while transcription of interleukin-1β involves an additional regulatory step resulting in increased heterogeneity. Despite different modes of regulation, systematic analysis of single-cell data for a range of genes demonstrates that the variability in transcript count is linearly constrained by the mean response over a range of conditions. Mathematical modeling of smFISH counts and experimental perturbation of chromatin state demonstrates that linear constraints emerge through modulation of transcriptional bursting along with gene-specific relationships. Overall, our analyses demonstrate that the variability of the inducible single-cell mRNA response is constrained by transcriptional bursting.

TCR signaling pathways cooperate to activate the inducible transcription factors NF-κB, NFAT, and AP-1. In this study, using the calcium ionophore ionomycin and/or PMA on Jurkat T cells, we show that the gene expression program associated with activation of TCR signaling is closely related to specific chromatin landscapes. We find that calcium and kinase signaling cooperate to induce chromatin remodeling at ∼2100 chromatin regions, which demonstrate enriched binding motifs for inducible factors and correlate with target gene expression. We found that these regions typically function as inducible enhancers. Many of these elements contain composite NFAT/AP-1 sites, which typically support cooperative binding, thus further reinforcing the need for cooperation between calcium and kinase signaling in the activation of genes in T cells. In contrast, treatment with PMA or ionomycin alone induces chromatin remodeling at far fewer regions (∼600 and ∼350, respectively), which mostly represent a subset of those induced by costimulation. This suggests that the integration of TCR signaling largely occurs at the level of chromatin, which we propose plays a crucial role in regulating T cell activation.

Long-acting subcutaneous lenacapavir (LEN), a first-in-class HIV capsid inhibitor approved by the US FDA for the treatment of multidrug-resistant HIV-1 with twice yearly dosing, is under investigation for HIV-1 pre-exposure prophylaxis (PrEP). We previously derived a simian-tropic HIV-1 clone (stHIV-A19) that encodes an HIV-1 capsid and replicates to high titres in pigtail macaques (PTM), resulting in a nonhuman primate model well-suited for evaluating LEN PrEP in vivo.

Because no currently available vaccine can prevent HIV infection, pre-exposure prophylaxis (PrEP) with antiretrovirals (ARVs) is an important tool for combating the HIV pandemic1,2. Long-acting ARVs promise to build on the success of current PrEP strategies, which must be taken daily, by reducing the frequency of administration3. GS-CA1 is a small-molecule HIV capsid inhibitor with picomolar antiviral potency against a broad array of HIV strains, including variants resistant to existing ARVs, and has shown long-acting therapeutic potential in a mouse model of HIV infection4. Here we show that a single subcutaneous administration of GS-CA1 provides long-term protection against repeated rectal simian-human immunodeficiency virus (SHIV) challenges in rhesus macaques. Whereas all control animals became infected after 15 weekly challenges, a single 300 mg kg-1 dose of GS-CA1 provided per-exposure infection risk reduction of 97% for 24 weeks. Pharmacokinetic analysis showed a correlation between GS-CA1 plasma concentration and protection from SHIV challenges. GS-CA1 levels greater than twice the rhesus plasma protein-adjusted 95% effective concentration conferred 100% protection in this model. These proof-of-concept data support the development of capsid inhibitors as a novel long-acting PrEP strategy in humans.

Despite its greener credentials, biomanufacturing remains financially uncompetitive compared with the higher carbon emitting, hydrocarbon-based chemical industry. Replacing traditional chassis such as E. coli with novel robust organisms, are a route to cost reduction for biomanufacturing. Extremophile bacteria such as the halophilic Halomonas bluephagenesis TD01 exemplify this potential by thriving in environments inherently inimical to other organisms, so reducing sterilisation costs. Novel chassis are inevitably less well annotated than established organisms. Rapid characterisation along with community data sharing will facilitate adoption of such organisms for biomanufacturing. The data record comprises a newly sequenced genome for the organism and evidence via LC-MS based proteomics for expression of 1160 proteins (30% of the proteome) including baseline quantification of 1063 proteins (27% of the proteome), and a spectral library enabling re-use for targeted LC-MS proteomics assays. Protein data are annotated with KEGG Orthology, enabling rapid matching of quantitative data to pathways of interest to biomanufacturing.

In response to stress, the translation of many mRNAs in yeast can change in a fashion discordant with the general repression of translation. Here, we use machine learning to mine the properties of these mRNAs to determine specific translation control signals. We find a strong association between transcripts acutely translationally repressed under oxidative stress and those associated with the RNA-binding protein Puf3p, a known regulator of cellular mRNAs encoding proteins targeted to mitochondria. Under oxidative stress, a PUF3 deleted strain exhibits more robust growth than wild-type cells and the shift in translation from polysomes to monosomes is attenuated, suggesting puf3Δ cells perceive less stress. In agreement, the ratio of reduced:oxidized glutathione, a major antioxidant and indicator of cellular redox state, is increased in unstressed puf3Δ cells but remains lower under stress. In untreated conditions, Puf3p migrates with polysomes rather than ribosome-free fractions, but this is lost under stress. Finally, reverse transcriptase-polymerase chain reaction (RT-PCR) of Puf3p targets following affinity purification shows Puf3p-mRNA associations are maintained or increased under oxidative stress. Collectively, these results point to Puf3p acting as a translational repressor in a manner exceeding the global translational response, possibly by temporarily limiting synthesis of new mitochondrial proteins as cells adapt to the stress.

Cells respond dynamically to pulsatile cytokine stimulation. Here we report that single, or well-spaced pulses of TNFα (>100 min apart) give a high probability of NF-κB activation. However, fewer cells respond to shorter pulse intervals (<100 min) suggesting a heterogeneous refractory state. This refractory state is established in the signal transduction network downstream of TNFR and upstream of IKK, and depends on the level of the NF-κB system negative feedback protein A20. If a second pulse within the refractory phase is IL-1β instead of TNFα, all of the cells respond. This suggests a mechanism by which two cytokines can synergistically activate an inflammatory response. Gene expression analyses show strong correlation between the cellular dynamic response and NF-κB-dependent target gene activation. These data suggest that refractory states in the NF-κB system constitute an inherent design motif of the inflammatory response and we suggest that this may avoid harmful homogenous cellular activation.

Monitoring the spread of viral pathogens in the population during epidemics is crucial for mounting an effective public health response. Understanding the viral lineages that constitute the infections in a population can uncover the origins and transmission patterns of outbreaks and detect the emergence of novel variants that may impact the course of an epidemic. Population-level surveillance of viruses through genomic sequencing of wastewater captures unbiased lineage data, including cryptic asymptomatic and undiagnosed infections, and has been shown to detect infection outbreaks and novel variant emergence before detection in clinical samples. Here, we present an optimised protocol for quantification and sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in influent wastewater, used for high-throughput genomic surveillance in England during the COVID-19 pandemic. This protocol utilises reverse compliment PCR for library preparation, enabling tiled amplification across the whole viral genome and sequencing adapter addition in a single step to enhance efficiency. Sequencing of synthetic SARS-CoV-2 RNA provided evidence validating the efficacy of this protocol, while data from high-throughput sequencing of wastewater samples demonstrated the sensitivity of this method. We also provided guidance on the quality control steps required during library preparation and data analysis. Overall, this represents an effective method for high-throughput sequencing of SARS-CoV-2 in wastewater which can be applied to other viruses and pathogens of humans and animals.

The selection and regulation of individual mRNAs for translation initiation from a competing pool of mRNA are poorly understood processes. The closed loop complex, comprising eIF4E, eIF4G and PABP, and its regulation by 4E-BPs are perceived to be key players. Using RIP-seq, we aimed to evaluate the role in gene regulation of the closed loop complex and 4E-BP regulation across the entire yeast transcriptome.

The use of next generation sequencing (NGS) to identify novel viral sequences from eukaryotic tissue samples is challenging. Issues can include the low proportion and copy number of viral reads and the high number of contigs (post-assembly), making subsequent viral analysis difficult. Comparison of assembly algorithms with pre-assembly host-mapping subtraction using a short-read mapping tool, a k-mer frequency based filter and a low complexity filter, has been validated for viral discovery with Illumina data derived from naturally infected liver tissue and simulated data. Assembled contig numbers were significantly reduced (up to 99.97%) by the application of these pre-assembly filtering methods. This approach provides a validated method for maximizing viral contig size as well as reducing the total number of assembled contigs that require down-stream analysis as putative viral nucleic acids.

Recent publications have described and applied a novel metric that quantifies the genetic distance of an individual with respect to two population samples, and have suggested that the metric makes it possible to infer the presence of an individual of known genotype in a sample for which only the marginal allele frequencies are known. However, the assumptions, limitations, and utility of this metric remained incompletely characterized. Here we present empirical tests of the method using publicly accessible genotypes, as well as analytical investigations of the method's strengths and limitations. The results reveal that the null distribution is sensitive to the underlying assumptions, making it difficult to accurately calibrate thresholds for classifying an individual as a member of the population samples. As a result, the false-positive rates obtained in practice are considerably higher than previously believed. However, despite the metric's inadequacies for identifying the presence of an individual in a sample, our results suggest potential avenues for future research on tuning this method to problems of ancestry inference or disease prediction. By revealing both the strengths and limitations of the proposed method, we hope to elucidate situations in which this distance metric may be used in an appropriate manner. We also discuss the implications of our findings in forensics applications and in the protection of GWAS participant privacy.

Translation factors eIF4E and eIF4G form eIF4F, which interacts with the messenger RNA (mRNA) 5' cap to promote ribosome recruitment and translation initiation. Variations in the association of eIF4F with individual mRNAs likely contribute to differences in translation initiation frequencies between mRNAs. As translation initiation is globally reprogrammed by environmental stresses, we were interested in determining whether eIF4F interactions with individual mRNAs are reprogrammed and how this may contribute to global environmental stress responses.

eIF4E-binding proteins (4E-BPs) regulate translation of mRNAs in eukaryotes. However the extent to which specific mRNA targets are regulated by 4E-BPs remains unknown. We performed translational profiling by microarray analysis of polysome and monosome associated mRNAs in wild-type and mutant cells to identify mRNAs in yeast regulated by the 4E-BPs Caf20p and Eap1p; the first-global comparison of 4E-BP target mRNAs. We find that yeast 4E-BPs modulate the translation of >1000 genes. Most target mRNAs differ between the 4E-BPs revealing mRNA specificity for translational control by each 4E-BP. This is supported by observations that eap1Δ and caf20Δ cells have different nitrogen source utilization defects, implying different mRNA targets. To account for the mRNA specificity shown by each 4E-BP, we found correlations between our data sets and previously determined targets of yeast mRNA-binding proteins. We used affinity chromatography experiments to uncover specific RNA-stabilized complexes formed between Caf20p and Puf4p/Puf5p and between Eap1p and Puf1p/Puf2p. Thus the combined action of each 4E-BP with specific 3'-UTR-binding proteins mediates mRNA-specific translational control in yeast, showing that this form of translational control is more widely employed than previously thought.

Wastewater-based epidemiology has been used extensively throughout the COVID-19 (coronavirus disease 19) pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public-health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants; yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants of concern (VOCs) (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15th and 18th December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers. Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.

The PUF family of RNA-binding proteins regulate gene expression post-transcriptionally. Saccharomyces cerevisiae Puf3p is characterised as binding nuclear-encoded mRNAs specifying mitochondrial proteins. Extensive studies of its regulation of COX17 demonstrate its role in mRNA decay. Using integrated genome-wide approaches we define an expanded set of Puf3p target mRNAs and quantitatively assessed the global impact of loss of PUF3 on gene expression using mRNA and polysome profiling and quantitative proteomics. In agreement with prior studies, our sequencing of affinity-purified Puf3-TAP associated mRNAs (RIP-seq) identified mRNAs encoding mitochondrially-targeted proteins. Additionally, we also found 720 new mRNA targets that predominantly encode proteins that enter the nucleus. Comparing transcript levels in wild-type and puf3∆ cells revealed that only a small fraction of mRNA levels alter, suggesting Puf3p determines mRNA stability for only a limited subset of its target mRNAs. Finally, proteomic and translatomic studies suggest that loss of Puf3p has widespread, but modest, impact on mRNA translation. Taken together our integrated multi-omics data point to multiple classes of Puf3p targets, which display coherent post-transcriptional regulatory properties and suggest Puf3p plays a broad, but nuanced, role in the fine-tuning of gene expression.