Alcohol shifts gut microbial networks and ameliorates a murine model of neuroinflammation in a sex-specific pattern.

Alcohol is a widely consumed dietary component by patients with autoimmune neuroinflammatory diseases, but current evidence on the effects of alcohol in these conditions is confounding. Epidemiological studies suggest moderate consumption of alcohol may be protective in some autoimmune diseases; however, this correlation has not been directly investigated. Here, we characterize the effects of moderate-dose alcohol in a model system of autoimmune neuroinflammation, experimental autoimmune encephalomyelitis (EAE). Male and female C57BL/6J mice were fed a 2.6% alcohol or isocaloric diet for 3 wk prior to MOG35-55 EAE induction. Surprisingly, alcohol-fed males experienced significantly greater disease remission compared to alcohol-fed females and control-fed counterparts. We observed a male-specific decrease in microglial density in alcohol-consuming animals in cervical and thoracic spinal cord in late-stage disease. In the gut, alcohol diet resulted in several sex-specific alterations in key microbiota known for their regulatory immune roles, including Turicibacter, Akkermansia, Prevotella, and Clostridium Using a correlation network modeling approach, we identified unique bacterial modules that are significantly enriched in response to treatment and sex, composed of Clostridial taxa and several Firmicutes known to be protective in EAE. Together, these data demonstrate the potential of alcohol to significantly alter the course of autoimmunity differentially in males and females via effects on gut bacterial networks and support further need to evaluate dose and sex-specific alcohol effects in multiple sclerosis (MS) and other autoimmune neuroinflammatory conditions.

Bioinformatic Analysis Underpinning the Frequent Occurrence of Immune Thrombocytopenic Purpura in COVID-19 Patients.

BACKGROUND: Secondary immune thrombocytopenic purpura (ITP) associated with coronavirus disease 2019 (COVID-19) is a rare but serious complication of the pandemic. Diagnostic criteria include clinical and laboratory findings. Early treatment is often effective, but rare severe bleeding and death can occur. An autoimmune mechanism is likely. OBJECTIVES: To determine a role for molecular mimicry in producing disease. METHODS: Hexapeptide and heptapeptide matches between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and platelet N-glycosylated proteins and other human proteins were assessed. RESULTS: Shared viral and platelet glycoprotein peptides were found. Copy frequency of these peptides in the human proteome was low for many of the candidate molecular mimics. CONCLUSIONS: The data support a contribution of molecular mimicry in COVID-19 ITP autoimmunity and offer avenues for in vitro diagnostic assay development. The continuation of the pandemic necessitates additional understanding of COVID-19 ITP as well as studies on diagnosis and mitigation.

A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients.

Extensive intratumoral heterogeneity (ITH) is believed to contribute to therapeutic failure and tumor recurrence, as treatment-resistant cell clones can survive and expand. However, little is known about ITH in triple-negative breast cancer (TNBC) because of the limited number of single-cell sequencing studies on TNBC. In this study, we explored ITH in TNBC by evaluating gene expression-derived and imaging-derived multi-region differences within the same tumor. We obtained tissue specimens from 10 TNBC patients and conducted RNA sequencing analysis of 2-4 regions per tumor. We developed a novel analysis framework to dissect and characterize different types of variability: between-patients (inter-tumoral heterogeneity), between-patients across regions (inter-tumoral and region heterogeneity), and within-patient, between-regions (regional intratumoral heterogeneity). We performed a Bayesian changepoint analysis to assess and classify regional variability as low (convergent) versus high (divergent) within each patient feature (TNBC and PAM50 subtypes, immune, stroma, tumor counts and tumor infiltrating lymphocytes). Gene expression signatures were categorized into three types of variability: between-patients (108 genes), between-patients across regions (183 genes), and within-patients, between-regions (778 genes). Based on the between-patient gene signature, we identified two distinct patient clusters that differed in menopausal status. Significant intratumoral divergence was observed for PAM50 classification, tumor cell counts, and tumor-infiltrating T cell abundance. Other features examined showed a representation of both divergent and convergent results. Lymph node stage was significantly associated with divergent tumors. Our results show extensive intertumoral heterogeneity and regional ITH in gene expression and image-derived features in TNBC. Our findings also raise concerns regarding gene expression based TNBC subtyping. Future studies are warranted to elucidate the role of regional heterogeneity in TNBC as a driver of treatment resistance.

SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing.

MOTIVATION: We set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score-fold-change, test-statistic, P-value-comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies non-parametric kernel smoothing to uncover promoter motif sites that correlate with elevated differential expression scores. SArKS detects motif k-mers by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motif sites can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing. RESULTS: We applied SArKS to published gene expression data representing distinct neocortical neuron classes in Mus musculus and interneuron developmental states in Homo sapiens. When benchmarked against several existing algorithms using a cross-validation procedure, SArKS identified larger motif sets that formed the basis for regression models with higher correlative power. AVAILABILITY AND IMPLEMENTATION: https://github.com/denniscwylie/sarks. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

eIFiso4G Augments the Synthesis of Specific Plant Proteins Involved in Normal Chloroplast Function.

The plant-specific translation initiation complex eIFiso4F is encoded by three genes in Arabidopsis (Arabidopsis thaliana)-genes encoding the cap binding protein eIFiso4E (eifiso4e) and two isoforms of the large subunit scaffolding protein eIFiso4G (i4g1 and i4g2). To quantitate phenotypic changes, a phenomics platform was used to grow wild-type and mutant plants (i4g1, i4g2, i4e, i4g1 x i4g2, and i4g1 x i4g2 x i4e [i4f]) under various light conditions. Mutants lacking both eIFiso4G isoforms showed the most obvious phenotypic differences from the wild type. Two-dimensional differential gel electrophoresis and mass spectrometry were used to identify changes in protein levels in plants lacking eIFiso4G. Four of the proteins identified as measurably decreased and validated by immunoblot analysis were two light harvesting complex binding proteins 1 and 3, Rubisco activase, and carbonic anhydrase. The observed decreased levels for these proteins were not the direct result of decreased transcription or protein instability. Chlorophyll fluorescence induction experiments indicated altered quinone reduction kinetics for the double and triple mutant plants with significant differences observed for absorbance, trapping, and electron transport. Transmission electron microscopy analysis of the chloroplasts in mutant plants showed impaired grana stacking and increased accumulation of starch granules consistent with some chloroplast proteins being decreased. Rescue of the i4g1 x i4g2 plant growth phenotype and increased expression of the validated proteins to wild-type levels was obtained by overexpression of eIFiso4G1. These data suggest a direct and specialized role for eIFiso4G in the synthesis of a subset of plant proteins.

Nineteen Years of Consistently Positive and Strong Female Mate Preferences despite Individual Variation.

Sexual selection driven by mate choice has generated some of the most astounding diversity in nature, suggesting that population-level preferences should be strong and consistent over many generations. On the other hand, mating preferences are among the least repeatable components of an individual animal's phenotype, suggesting that consistency should be low across an animal's lifetime. Despite decades of intensive study of sexual selection, there is almost no information about the strength and consistency of preferences across many years. In this study, we present the results of more than 5,000 mate choice tests with a species of wild frog conducted over 19 consecutive years. Results show that preferences are positive and strong and vary little across years. This consistency occurs despite the fact that there are substantial differences among females in their strength of preference. We also suggest that mate preferences in populations that are primarily the result of sensory exploitation might be more stable over time than preferences that are primarily involved in assessing male quality.

Quantitative filter forensics with residential HVAC filters to assess indoor concentrations.

Analysis of the dust from heating, ventilation, and air conditioning (HVAC) filters is a promising long-term sampling method to characterize airborne particle-bound contaminants. This filter forensics (FF) approach provides valuable insights about differences between buildings, but does not allow for an estimation of indoor concentrations. In this investigation, FF is extended to quantitative filter forensics (QFF) by using measurements of the volume of air that passes through the filter and the filter efficiency, to assess the integrated average airborne concentrations of total fungal and bacterial DNA, 36 fungal species, endotoxins, phthalates, and organophosphate esters (OPEs) based on dust extracted from HVAC filters. Filters were collected from 59 homes located in central Texas, USA, after 1 month of deployment in each summer and winter. Results showed considerable differences in the concentrations of airborne particle-bound contaminants in studied homes. The airborne concentrations for most of the analytes are comparable with those reported in the literature. In this sample of homes, the HVAC characterization measurements varied much less between homes than the variation in the filter dust concentration of each analyte, suggesting that even in the absence of HVAC data, FF can provide insight about concentration differences for homes with similar HVAC systems.

Conserved Sequence Preferences Contribute to Substrate Recognition by the Proteasome.

The proteasome has pronounced preferences for the amino acid sequence of its substrates at the site where it initiates degradation. Here, we report that modulating these sequences can tune the steady-state abundance of proteins over 2 orders of magnitude in cells. This is the same dynamic range as seen for inducing ubiquitination through a classic N-end rule degron. The stability and abundance of His3 constructs dictated by the initiation site affect survival of yeast cells and show that variation in proteasomal initiation can affect fitness. The proteasome's sequence preferences are linked directly to the affinity of the initiation sites to their receptor on the proteasome and are conserved between Saccharomyces cerevisiae, Schizosaccharomyces pombe, and human cells. These findings establish that the sequence composition of unstructured initiation sites influences protein abundance in vivo in an evolutionarily conserved manner and can affect phenotype and fitness.

A microRNA-based test improves endoscopic ultrasound-guided cytologic diagnosis of pancreatic cancer.

BACKGROUND & AIMS: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) in combination with cytopathology is the optimal method for diagnosis and staging of pancreatic ductal adenocarcinoma (PDAC) and other pancreatic lesions. Its clinical utility, however, can be limited by high rates of indeterminate or false-negative results. We aimed to develop and validate a microRNA (miRNA)-based test to improve preoperative detection of PDAC. METHODS: Levels of miRNAs were analyzed in a centralized clinical laboratory by relative quantitative polymerase chain reaction in 95 formalin-fixed paraffin-embedded specimens and 228 samples collected by EUS-FNA during routine evaluations of patients with solid pancreatic masses at 4 institutions in the United States, 1 in Canada, and 1 in Poland. RESULTS: We developed a 5-miRNA expression classifier, consisting of MIR24, MIR130B, MIR135B, MIR148A, and MIR196, that could identify PDAC in well-characterized, formalin-fixed, paraffin-embedded specimens. Detection of PDAC in EUS-FNA samples increased from 78.8% by cytology analysis alone (95% confidence interval, 72.2%-84.5%) to 90.8% when combined with miRNA analysis (95% confidence interval, 85.6%-94.5%). The miRNA classifier correctly identified 22 additional true PDAC cases among 39 samples initially classified as benign, indeterminate, or nondiagnostic by cytology. Cytology and miRNA test results each were associated significantly with PDAC (P < .001), with positive predictive values greater than 99% (95% confidence interval, 96%-100%). CONCLUSIONS: We developed and validated a 5-miRNA classifier that can accurately predict which preoperative pancreatic EUS-FNA specimens contain PDAC. This test might aid in the diagnosis of pancreatic cancer by reducing the number of FNAs without a definitive adenocarcinoma diagnosis, thereby reducing the number of repeat EUS-FNA procedures.

High-Resolution Substrate Specificity Profiling of SARS-CoV-2 Mpro; Comparison to SARS-CoV Mpro.

The SARS-CoV-2 Mpro protease from COVID-19 cleaves the pp1a and pp2b polyproteins at 11 sites during viral maturation and is the target of Nirmatrelvir, one of the two components of the frontline treatment sold as Paxlovid. We used the YESS 2.0 platform, combining protease and substrate expression in the yeast endoplasmic reticulum with fluorescence-activated cell sorting and next-generation sequencing, to carry out the high-resolution substrate specificity profiling of SARS-CoV-2 Mpro as well as the related SARS-CoV Mpro from SARS 2003. Even at such a high level of resolution, the substrate specificity profiles of both enzymes are essentially identical. The population of cleaved substrates isolated in our sorts is so deep, the relative catalytic efficiencies of the different cleavage sites on the SARS-CoV-2 polyproteins pp1a and pp2b are qualitatively predicted. These results not only demonstrated the precise and reproducible nature of the YESS 2.0/NGS approach to protease substrate specificity profiling but also should be useful in the design of next generation SARS-CoV-2 Mpro inhibitors, and by analogy, SARS-CoV Mpro inhibitors as well.

Molecular Mimicry as a Mechanism of Viral Immune Evasion and Autoimmunity.

Mimicry of host protein structures ("molecular mimicry") is a common mechanism employed by viruses to evade the host's immune system. To date, studies have primarily evaluated molecular mimicry in the context of full protein structural mimics. However, recent work has demonstrated that short linear amino acid (AA) molecular mimics can elicit cross-reactive antibodies and T-cells from the host, which may contribute to development and progression of autoimmunity. Despite this, the prevalence of molecular mimics throughout the human virome has not been fully explored. In this study, we evaluate 134 human infecting viruses and find significant usage of linear mimicry across the virome, particularly those in the herpesviridae and poxviridae families. Furthermore, we identify that proteins involved in cellular replication and inflammation, those expressed from autosomes, the X chromosome, and in thymic cells are over-enriched in viral mimicry. Finally, we demonstrate that short linear mimicry from Epstein-Barr virus (EBV) is significantly higher in auto-antibodies found in multiple sclerosis patients to a greater degree than previously appreciated. Our results demonstrate that human-infecting viruses frequently leverage mimicry in the course of their infection, point to substantial evolutionary pressure for mimicry, and highlight mimicry's important role in human autoimmunity. Clinically, our findings could translate to development of novel therapeutic strategies that target viral infections linked to autoimmunity, with the goal of eliminating disease-associated latent viruses and preventing their reactivation.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood.

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Clinical characteristics of Long COVID patients presenting to a dedicated academic post-COVID-19 clinic in Central Texas.

Post-acute sequelae SARS-CoV-2 (PASC), also known as Long COVID, is a complex and widely recognized illness with estimates ranging from 5 to 30% of all COVID-19 cases. We performed a retrospective chart review of patients who presented to a dedicated Post-COVID-19 clinic between June 2021 and May 2022. The median patient age was 44.5 years, 63.5% patients were female, and patients presented at a median of 10.4 months from acute COVD-19 infection. 78% self-identified their race as white, and 21% identified as Latino ethnicity. During the acute COVID-19 infection, 50% of patients experienced moderate disease severity and 10.5% were hospitalized. The top three co-morbid conditions prior to SARS-CoV-2 infection included mental health conditions, hypertension and asthma. Patients reported a median of 18 new symptoms following COVID-19 illness, the most common were fatigue (89%), forgetfulness or "brain fog" (89%), and difficulty concentrating (77%). MoCA (Montreal Cognitive Assessment) assessment demonstrated that 46% had mild cognitive dysfunction. PHQ-9 (Patient Health Questionnaire) testing revealed 42% had moderate to severe depression, and 38% had moderate to severe anxiety on the GAD-7 (Generalized Anxiety Disorder) assessment. Symptom burden was similar across gender, age, and initial disease severity. PASC patients presenting to an academic Post-COVID-19 clinic experienced numerous multisystem symptoms and functional impairment, independent of the initial COVID-19 disease severity.

Comparison of commercial DNA extraction kits for whole metagenome sequencing of human oral, vaginal, and rectal microbiome samples.

Introduction: Advancements in DNA extraction and sequencing technologies have been fundamental in deciphering the significance of the microbiome related to human health and pathology. Whole metagenome shotgun sequencing (WMS) is gaining popularity in use compared to its predecessor (i.e., amplicon-based approaches). However, like amplicon-based approaches, WMS is subject to bias from DNA extraction methods that can compromise the integrity of sequencing and subsequent findings. The purpose of this study was to evaluate systematic differences among four commercially available DNA extraction kits frequently used for WMS analysis of the microbiome. Methods: Oral, vaginal, and rectal swabs were collected in replicates of four by a healthcare provider from five participants and randomized to one of four DNA extraction kits. Two extraction blanks and three replicate mock community samples were also extracted using each extraction kit. WMS was completed with NovaSeq 6000 for all samples. Sequencing and microbial communities were analyzed using nonmetric multidimensional scaling and compositional bias analysis. Results: Extraction kits differentially biased the percentage of reads attributed to microbial taxa across samples and body sites. The PowerSoil Pro kit performed best in approximating expected proportions of mock communities. While HostZERO was biased against gram-negative bacteria, the kit outperformed other kits in extracting fungal DNA. In clinical samples, HostZERO yielded a smaller fraction of reads assigned to Homo sapiens across sites and had a higher fraction of reads assigned to bacterial taxa compared to other kits. However, HostZERO appears to bias representation of microbial communities and demonstrated the most dispersion by site, particularly for vaginal and rectal samples. Conclusions: Systematic differences exist among four frequently referenced DNA extraction kits when used for WMS analysis of the human microbiome. Consideration of such differences in study design and data interpretation is imperative to safeguard the integrity of microbiome research and reproducibility of results.

Inflammatory breast cancer biomarker identification by simultaneous TGIRT-seq profiling of coding and non-coding RNAs in tumors and blood.

Inflammatory breast cancer (IBC) is the most aggressive and lethal breast cancer subtype, but lags in biomarker identification. Here, we used an improved Thermostable Group II Intron Reverse Transcriptase RNA sequencing (TGIRT-seq) method to simultaneously profile coding and non-coding RNAs from tumors, PBMCs, and plasma of IBC and non-IBC patients and healthy donors. Besides RNAs from known IBC-relevant genes, we identified hundreds of other overexpressed coding and non-coding RNAs (p≤0.001) in IBC tumors and PBMCs, including higher proportions with elevated intron-exon depth ratios (IDRs), likely reflecting enhanced transcription resulting in accumulation of intronic RNAs. As a consequence, differentially represented protein-coding gene RNAs in IBC plasma were largely intron RNA fragments, whereas those in healthy donor and non-IBC plasma were largely fragmented mRNAs. Potential IBC biomarkers in plasma included T-cell receptor pre-mRNA fragments traced to IBC tumors and PBMCs; intron RNA fragments correlated with high IDR genes; and LINE-1 and other retroelement RNAs that we found globally up-regulated in IBC and preferentially enriched in plasma. Our findings provide new insights into IBC and demonstrate advantages of broadly analyzing transcriptomes for biomarker identification. The RNA-seq and data analysis methods developed for this study may be broadly applicable to other diseases.

Dissecting Clinical Features of COVID-19 in a Cohort of 21,312 Acute Care Patients.

COVID-19 has resulted in over 645 million hospitalization and 7 million deaths globally. However, many questions still remain about clinical complications in COVID-19 and if these complications changed with different circulating SARS-CoV-2 strains. We analyzed a 2.5-year retrospective cohort of 47,063 encounters for 21,312 acute care patients at five Central Texas hospitals and define distinct trajectory groups (TGs) with latent class mixed modeling, based on the World Health Organization COVID-19 Ordinal Scale. Using this TG framework, we evaluated the association of demographics, diagnoses, vitals, labs, imaging, consultations, and medications with COVID-19 severity and broad clinical outcomes. Patients within 6 distinct TGs differed in manifestations of multi-organ disease and multiple clinical factors. The proportion of mild patients increased over time, particularly during Omicron waves. Age separated mild and fatal patients, though did not distinguish patients with severe versus critical disease. Male and Hispanic/Latino demographics were associated with more severe/critical TGs. More severe patients had a higher rate of neuropsychiatric diagnoses, consultations, and brain imaging, which did not change significantly in severe patients across SARS-CoV-2 variant waves. More severely affected patients also demonstrated an immunological signature of high neutrophils and immature granulocytes, and low lymphocytes and monocytes. Interestingly, low albumin was one of the best lab predictors of COVID-19 severity in association with higher malnutrition in severe/critical patients, raising concern of nutritional insufficiency influencing COVID-19 outcomes. Despite this, only a small fraction of severe/critical patients had nutritional labs checked (pre-albumin, thiamine, Vitamin D, B vitamins) or received targeted interventions to address nutritional deficiencies such as vitamin replacement. Our findings underscore the significant link between COVID-19 severity, neuropsychiatric complications, and nutritional insufficiency as key risk factors of COVID-19 outcomes and raise the question of the need for more widespread early assessment of patients' neurological, psychiatric, and nutritional status in acute care settings to help identify those at risk of severe disease outcomes.

Apobec-Mediated Retroviral Hypermutation In Vivo is Dependent on Mouse Strain.

Replication of the complex retrovirus mouse mammary tumor virus (MMTV) is antagonized by murine Apobec3 (mA3), a member of the Apobec family of cytidine deaminases. We have shown that MMTV-encoded Rem protein inhibits proviral mutagenesis by the Apobec enzyme, activation-induced cytidine deaminase (AID) during viral replication in BALB/c mice. To further study the role of Rem in vivo , we have infected C57BL/6 (B6) mice with a superantigen-independent lymphomagenic strain of MMTV (TBLV-WT) or a mutant strain (TBLV-SD) that is defective in Rem and its cleavage product Rem-CT. Unlike MMTV, TBLV induced T-cell tumors in µMT mice, indicating that mature B cells, which express the highest AID levels, are not required for TBLV replication. Compared to BALB/c, B6 mice were more susceptible to TBLV infection and tumorigenesis. The lack of Rem expression accelerated B6 tumorigenesis at limiting doses compared to TBLV-WT in either wild-type B6 or AID-deficient mice. However, unlike proviruses from BALB/c mice, high-throughput sequencing indicated that proviral G-to-A or C-to-T changes did not significantly differ in the presence and absence of Rem expression. Ex vivo stimulation showed higher levels of mA3 relative to AID in B6 compared to BALB/c splenocytes, but effects of agonists differed in the two strains. RNA-Seq revealed increased transcripts related to growth factor and cytokine signaling in TBLV-SD-induced tumors relative to those from TBLV-WT, consistent with a third Rem function. Thus, Rem-mediated effects on tumorigenesis in B6 mice are independent of Apobec-mediated proviral hypermutation.

SARS-CoV-2 Humoral Immune Responses in Convalescent Individuals Over 12 Months Reveal Severity-Dependent Antibody Dynamics.

Background: Understanding the kinetics and longevity of antibody responses to SARS-CoV-2 is critical to informing strategies toward reducing Coronavirus disease 2019 (COVID-19) reinfections, and improving vaccination and therapy approaches. Methods: We evaluated antibody titers against SARS-CoV-2 nucleocapsid (N), spike (S), and receptor binding domain (RBD) of spike in 98 convalescent participants who experienced asymptomatic, mild, moderate or severe COVID-19 disease and in 17 non-vaccinated, non-infected controls, using four different antibody assays. Participants were sampled longitudinally at 1, 3, 6, and 12 months post-SARS-CoV-2 positive PCR test. Findings: Increasing acute COVID-19 disease severity correlated with higher anti-N and anti-RBD antibody titers throughout 12 months post-infection. Anti-N and anti-RBD titers declined over time in all participants, with the exception of increased anti-RBD titers post-vaccination, and the decay rates were faster in hospitalized compared to non-hospitalized participants. <50% of participants retained anti-N titers above control levels at 12 months, with non-hospitalized participants falling below control levels sooner. Nearly all hospitalized and non-hospitalized participants maintained anti-RBD titers above controls for up to 12 months, suggesting longevity of protection against severe reinfections. Nonetheless, by 6 months, few participants retained >50% of their 1-month anti-N or anti-RBD titers. Vaccine-induced increases in anti-RBD titers were greater in non-hospitalized relative to hospitalized participants. Early convalescent antibody titers correlated with age, but no association was observed between Post-Acute Sequelae of SARS-CoV-2 infection (PASC) status or acute steroid treatment and convalescent antibody titers. Interpretation: Hospitalized participants developed higher anti-SARS-CoV-2 antibody titers relative to non-hospitalized participants, a difference that persisted throughout 12 months, despite the faster decline in titers in hospitalized participants. In both groups, while anti-N titers fell below control levels for at least half of the participants, anti-RBD titers remained above control levels for almost all participants over 12 months, demonstrating generation of long-lived antibody responses known to correlate with protection from severe disease across COVID-19 severities. Overall, our findings contribute to the evolving understanding of COVID-19 antibody dynamics. Funding: Austin Public Health, NIAAA, Babson Diagnostics, Dell Medical School Startup.

Covalent JNK Inhibitor, JNK-IN-8, Suppresses Tumor Growth in Triple-Negative Breast Cancer by Activating TFEB- and TFE3-Mediated Lysosome Biogenesis and Autophagy.

The heterogeneity and aggressiveness of triple-negative breast cancer (TNBC) contribute to its early recurrence and metastasis. Despite substantial research to identify effective therapeutic targets, TNBC remains elusive in terms of improving patient outcomes. Here, we report that a covalent JNK inhibitor, JNK-IN-8, suppresses TNBC growth both in vitro and in vivo. JNK-IN-8 reduced colony formation, cell viability, and organoid growth in vitro and slowed patient-derived xenograft and syngeneic tumor growth in vivo. Cells treated with JNK-IN-8 exhibited large, cytoplasmic vacuoles with lysosomal markers. To examine the molecular mechanism of this phenotype, we looked at the master regulators of lysosome biogenesis and autophagy transcription factor EB (TFEB) and TFE3. JNK-IN-8 inhibited TFEB phosphorylation and induced nuclear translocation of unphosphorylated TFEB and TFE3. This was accompanied by an upregulation of TFEB/TFE3 target genes associated with lysosome biogenesis and autophagy. Depletion of both TFEB and TFE3 diminished the JNK-IN-8-driven upregulation of lysosome biogenesis and/or autophagy markers. TFEB and TFE3 are phosphorylated by a number of kinases, including mTOR. JNK-IN-8 reduced phosphorylation of mTOR targets in a concentration-dependent manner. Knockout of JNK1 and/or JNK2 had no impact on TFEB/TFE3 activation or mTOR inhibition by JNK-IN-8 but inhibited colony formation. Similarly, reexpression of either wildtype or drug-nonbinding JNK (C116S) in JNK knockout cells did not reverse JNK-IN-8-induced TFEB dephosphorylation. In summary, JNK-IN-8 induced lysosome biogenesis and autophagy by activating TFEB/TFE3 via mTOR inhibition independently of JNK. Together, these findings demonstrate the efficacy of JNK-IN-8 as a targeted therapy for TNBC and reveal its novel lysosome- and autophagy-mediated mechanism of action.

Massively Parallel Selection of NanoCluster Beacons.

NanoCluster Beacons (NCBs) are multicolor silver nanocluster probes whose fluorescence can be activated or tuned by a proximal DNA strand called the activator. While a single-nucleotide difference in a pair of activators can lead to drastically different activation outcomes, termed polar opposite twins (POTs), it is difficult to discover new POT-NCBs using the conventional low-throughput characterization approaches. Here, a high-throughput selection method is reported that takes advantage of repurposed next-generation-sequencing chips to screen the activation fluorescence of ≈40 000 activator sequences. It is found that the nucleobases at positions 7-12 of the 18-nucleotide-long activator are critical to creating bright NCBs and positions 4-6 and 2-4 are hotspots to generate yellow-orange and red POTs, respectively. Based on these findings, a "zipper-bag" model is proposed that can explain how these hotspots facilitate the formation of distinct silver cluster chromophores and alter their chemical yields. Combining high-throughput screening with machine-learning algorithms, a pipeline is established to design bright and multicolor NCBs in silico.