Lung epithelial and endothelial damage, loss of tissue repair, inhibition of fibrinolysis, and cellular senescence in fatal COVID-19.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is characterized by respiratory distress, multiorgan dysfunction, and, in some cases, death. The pathological mechanisms underlying COVID-19 respiratory distress and the interplay with aggravating risk factors have not been fully defined. Lung autopsy samples from 18 patients with fatal COVID-19, with symptom onset-to-death times ranging from 3 to 47 days, and antemortem plasma samples from 6 of these cases were evaluated using deep sequencing of SARS-CoV-2 RNA, multiplex plasma protein measurements, and pulmonary gene expression and imaging analyses. Prominent histopathological features in this case series included progressive diffuse alveolar damage with excessive thrombosis and late-onset pulmonary tissue and vascular remodeling. Acute damage at the alveolar-capillary barrier was characterized by the loss of surfactant protein expression with injury to alveolar epithelial cells, endothelial cells, respiratory epithelial basal cells, and defective tissue repair processes. Other key findings included impaired clot fibrinolysis with increased concentrations of plasma and lung plasminogen activator inhibitor-1 and modulation of cellular senescence markers, including p21 and sirtuin-1, in both lung epithelial and endothelial cells. Together, these findings further define the molecular pathological features underlying the pulmonary response to SARS-CoV-2 infection and provide important insights into signaling pathways that may be amenable to therapeutic intervention.

Core and region-enriched networks of behaviorally regulated genes and the singing genome.

Songbirds represent an important model organism for elucidating molecular mechanisms that link genes with complex behaviors, in part because they have discrete vocal learning circuits that have parallels with those that mediate human speech. We found that ~10% of the genes in the avian genome were regulated by singing, and we found a striking regional diversity of both basal and singing-induced programs in the four key song nuclei of the zebra finch, a vocal learning songbird. The region-enriched patterns were a result of distinct combinations of region-enriched transcription factors (TFs), their binding motifs, and presinging acetylation of histone 3 at lysine 27 (H3K27ac) enhancer activity in the regulatory regions of the associated genes. RNA interference manipulations validated the role of the calcium-response transcription factor (CaRF) in regulating genes preferentially expressed in specific song nuclei in response to singing. Thus, differential combinatorial binding of a small group of activity-regulated TFs and predefined epigenetic enhancer activity influences the anatomical diversity of behaviorally regulated gene networks.

New meta-analysis tools reveal common transcriptional regulatory basis for multiple determinants of behavior.

A fundamental problem in meta-analysis is how to systematically combine information from multiple statistical tests to rigorously evaluate a single overarching hypothesis. This problem occurs in systems biology when attempting to map genomic attributes to complex phenotypes such as behavior. Behavior and other complex phenotypes are influenced by intrinsic and environmental determinants that act on the transcriptome, but little is known about how these determinants interact at the molecular level. We developed an informatic technique that identifies statistically significant meta-associations between gene expression patterns and transcription factor combinations. Deploying this technique for brain transcriptome profiles from ca. 400 individual bees, we show that diverse determinants of behavior rely on shared combinations of transcription factors. These relationships were revealed only when we considered complex and variable regulatory rules, suggesting that these shared transcription factors are used in distinct ways by different determinants. This regulatory code would have been missed by traditional gene coexpression or cis-regulatory analytic methods. We expect that our meta-analysis tools will be useful for a broad array of problems in systems biology and other fields.

The transcription factor ultraspiracle influences honey bee social behavior and behavior-related gene expression.

Behavior is among the most dynamic animal phenotypes, modulated by a variety of internal and external stimuli. Behavioral differences are associated with large-scale changes in gene expression, but little is known about how these changes are regulated. Here we show how a transcription factor (TF), ultraspiracle (usp; the insect homolog of the Retinoid X Receptor), working in complex transcriptional networks, can regulate behavioral plasticity and associated changes in gene expression. We first show that RNAi knockdown of USP in honey bee abdominal fat bodies delayed the transition from working in the hive (primarily "nursing" brood) to foraging outside. We then demonstrate through transcriptomics experiments that USP induced many maturation-related transcriptional changes in the fat bodies by mediating transcriptional responses to juvenile hormone. These maturation-related transcriptional responses to USP occurred without changes in USP's genomic binding sites, as revealed by ChIP-chip. Instead, behaviorally related gene expression is likely determined by combinatorial interactions between USP and other TFs whose cis-regulatory motifs were enriched at USP's binding sites. Many modules of JH- and maturation-related genes were co-regulated in both the fat body and brain, predicting that usp and cofactors influence shared transcriptional networks in both of these maturation-related tissues. Our findings demonstrate how "single gene effects" on behavioral plasticity can involve complex transcriptional networks, in both brain and peripheral tissues.