Campylobacter jejuni is the leading cause of bacterial gastroenteritis in humans, but relatively little is known about the global regulation of virulence factors during infection of chickens or humans. This study identified DNA supercoiling as playing a key role in regulating motility and flagellar protein production and found that this supercoiling-controlled regulon is induced by growth in chicken mucus. A direct correlation was observed between motility and resting DNA supercoiling levels in different strains of C. jejuni, and relaxation of DNA supercoiling resulted in decreased motility. Transcriptional analysis and Western immunoblotting revealed that a reduction in motility and DNA supercoiling affected the two-component regulatory system FlgRS and was associated with reduced FlgR expression, increased FlgS expression, and aberrant expression of flagellin subunits. Electron microscopy revealed that the flagellar structure remained intact. Growth in the presence of porcine mucin resulted in increased negative supercoiling, increased motility, increased FlgR expression, and reduced FlgS expression. Finally, this supercoiling-dependent regulon was shown to be induced by growth in chicken mucus, and the level of activation was dependent on the source of the mucus from within the chicken intestinal tract. In conclusion, this study reports for the first time the key role played by DNA supercoiling in regulating motility in C. jejuni and indicates that the induction of this supercoiling-induced regulon in response to mucus from different sources could play a critical role in regulating motility in vivo.

BackgroundSex and age strongly influence the pathophysiology of human lungs, but scarce information is available about their effects on pulmonary gene expression.MethodsWe followed a discovery-validation strategy to identify sex- and age-related transcriptional differences in lung.ResultsWe identified transcriptional profiles significantly associated with sex (215 genes; FDR < 0.05) and age at surgery (217 genes) in non-involved lung tissue resected from 284 lung adenocarcinoma patients. When these profiles were tested in three independent series of non-tumor lung tissue from an additional 1,111 patients, we validated the association with sex and age for 25 and 22 genes, respectively. Among the 17 sex-biased genes mapping on chromosome X, 16 have been reported to escape X-chromosome inactivation in other tissues or cells, suggesting that this mechanism influences lung transcription too. Our 22 age-related genes partially overlap with genes modulated by age in other tissues, suggesting that the aging process has similar consequences on gene expression in different organs. Finally, seven genes whose expression was modulated by sex in non-tumor lung tissue, but no age-related gene, were also validated using publicly available data from 990 lung adenocarcinoma samples, suggesting that the physiological regulatory mechanisms are only partially active in neoplastic tissue.ConclusionsGene expression in non-tumor lung tissue is modulated by both sex and age. These findings represent a validated starting point for research on the molecular mechanisms underlying the observed differences in the course of lung diseases among men and women of different ages.

Many single nucleotide polymorphisms (SNPs) have been associated with lung cancer but lack confirmation and functional characterization. We retested the association of 56 candidate SNPs with lung adenocarcinoma risk and overall survival in a cohort of 823 Italian patients and 779 healthy controls, and assessed their function as expression quantitative trait loci (eQTLs). In the replication study, eight SNPs (rs401681, rs3019885, rs732765, rs2568494, rs16969968, rs6495309, rs11634351, and rs4105144) associated with lung adenocarcinoma risk and three (rs9557635, rs4105144, and rs735482) associated with survival. Five of these SNPs acted as cis-eQTLs, being associated with the transcription of IREB2 (rs2568494, rs16969968, rs11634351, rs6495309), PSMA4 (rs6495309) and ERCC1 (rs735482), out of 10,821 genes analyzed in lung. For these three genes, we obtained experimental evidence of differential allelic expression in lung tissue, pointing to the existence of in-cis genomic variants that regulate their transcription. These results suggest that these SNPs exert their effects on cancer risk/outcome through the modulation of mRNA levels of their target genes.The study of genetic factors modulating an individual's predisposition to lung cancer is supported by strong epidemiological evidence obtained from various types of studies. Observational studies have consistently reported an increased risk of lung cancer in first-degree relatives of lung cancer patients 1-5 . Genome-wide association studies (GWAS) on population-based series identified three main susceptibility loci, at 5p15 6-8 , 6p21 6 , and 15q25. The locus at 15q25 harbors genes for three nicotinic acetylcholine receptor subunits (CHRNA3, CHRNA5, and CHRNB4) that have previously been associated with lung cancer risk and nicotine dependence 6,9,10 . Other GWAS found many single nucleotide polymorphisms (SNPs) that associated with lung cancer risk [11][12][13][14][15][16] . However, the results obtained in these studies have not generally been confirmed, even in a large consortium study 17 .Some genetic variants associated with lung cancer risk have also been associated with prognosis. For instance, a polymorphism (rs6495309) in the promoter of CHRNA3 gene has been reported to be associated with the overall survival of patients with early-stage non-small-cell lung cancer (NSCLC) 18 . Moreover, rs667282 in CHRNA5 has recently been proposed as a modifier of prognosis in advanced NSCLC 19 . Several other SNPs, found using a GWAS approach, were proposed to be associated with prognosis or survival of lung cancer patients in different populations [20][21][22][23] . However, these studies did not identify the same candidate polymorphisms, which may be due (at least in part) to the wide genetic heterogeneity of the human population.The GWAS cited here, which aimed to find SNPs associated with lung cancer risk or prognosis, identified mostly non-overlapping subsets of SNPs, hindering progress in lung cancer research. One limitation of these studies is that they investigate...

Read-through transcripts result from the continuous transcription of adjacent, similarly oriented genes, with the splicing out of the intergenic region. They have been found in several neoplastic and normal tissues, but their pathophysiological significance is unclear. We used high-throughput sequencing of cDNA fragments (RNA-Seq) to identify read-through transcripts in the non-involved lung tissue of 64 surgically treated lung adenocarcinoma patients. A total of 52 distinct read-through species was identified, with 24 patients having at least one read-through event, up to a maximum of 17 such transcripts in one patient. Sanger sequencing validated 28 of these transcripts and identified an additional 15, for a total of 43 distinct read-through events involving 35 gene pairs. Expression levels of 10 validated read-through transcripts were measured by quantitative PCR in pairs of matched non-involved lung tissue and lung adenocarcinoma tissue from 45 patients. Higher expression levels were observed in normal lung tissue than in the tumor counterpart, with median relative quantification ratios between normal and tumor varying from 1.90 to 7.78; the difference was statistically significant (P < 0.001, Wilcoxon's signed-rank test for paired samples) for eight transcripts: ELAVL1–TIMM44, FAM162B–ZUFSP, IFNAR2–IL10RB, INMT–FAM188B, KIAA1841–C2orf74, NFATC3–PLA2G15, SIRPB1–SIRPD, and SHANK3–ACR. This report documents the presence of read-through transcripts in apparently normal lung tissue, with inter-individual differences in patterns and abundance. It also shows their down-regulation in tumors, suggesting that these chimeric transcripts may function as tumor suppressors in lung tissue.

Germline variants in genes involved in SARS-CoV-2 cell entry and in host innate immune responses to viruses may influence the susceptibility to infection. This study used whole-genome analyses of lung tissue to identify polymorphisms acting as expression quantitative trait loci (eQTLs) for 60 genes of relevance to SARS-CoV-2 infection susceptibility. The expression of genes with confirmed or possible roles in viral entry–replication and in host antiviral responses was studied in the non-diseased lung tissue of 408 lung adenocarcinoma patients. No gene was differently expressed by sex, but APOBEC3H levels were higher and PARP12 levels lower in older individuals. A total of 125 cis -eQTLs (false discovery rate < 0.05) was found to modulate mRNA expression of 15 genes ( ABO, ANPEP, AP2A2, APOBEC3D, APOBEC3G, BSG, CLEC4G, DDX58, DPP4, FURIN, FYCO1, RAB14, SERINC3, TRIM5, ZCRB1 ). eQTLs regulating ABO and FYCO1 were found in COVID-19 susceptibility loci. No trans -eQTLs were identified. Genetic control of the expression of these 15 genes, which encode putative virus receptors, proteins required for vesicle trafficking, enzymes that interfere with viral replication, and other restriction factors, may underlie interindividual differences in risk or severity of infection with SARS-CoV-2 or other viruses.

Background In bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. Results We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. Conclusions Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

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Germline variants in genes involved in SARS-CoV-2 cell entry (i.e. ACE2 and TMPRSS2) may influence the susceptibility to infection, as may polymorphisms in genes involved in the innate host response to viruses (e.g. APOBEC3 family). We searched for polymorphisms acting, in lung tissue, as expression quantitative trait loci (eQTLs) for 15 candidate COVID-19 susceptibility genes, selected for their roles in virus cell entry and host antiviral responses. No significant eQTLs were identified for ACE2 and TMPRSS2 genes, whose expression levels did not associate with either sex or age of the 408 patients whose non-diseased lung tissue was analyzed. Instead, we identified seven cis-eQTLs (FDR<0.05) for APOBEC3D and APOBEC3G (rs139296, rs9611092, rs139331, rs8177832, rs17537581, rs61362448, and rs738469). The genetic control of the expression of APOBEC3 genes, which encode enzymes that interfere with virus replication, may explain interindividual differences in risk or severity of viral infections. Future studies should investigate the role of host genetics in COVID-19 patients using a genome-wide approach, to identify other genes whose expression levels are associated with susceptibility to SARS-CoV-2 infection or COVID-19 severity.Author summaryIdentification of expression quantitative trait loci (eQTLs) has become commonplace in functional studies on the role of individual genetic variants in susceptibility to diseases. In COVID-19, it has been proposed that individual variants in SARS-CoV-2 cell entry and innate host response genes may influence the susceptibility to infection. We searched for polymorphisms acting, in non-diseased lung tissue of 408 patients, as eQTLs for 15 candidate COVID-19 susceptibility genes, selected for their roles in virus cell entry and host antiviral responses. Seven cis-eQTLs were detected for APOBEC3D and APOBEC3G genes, which encode enzymes that interfere with virus replication. No significant eQTLs were identified for ACE2 and TMPRSS2 genes. Therefore, the identified eQTLs may represent candidate loci modulating interindividual differences in risk or severity of SARS-CoV-2 virus infection.