The influence of the larval microbiome on susceptibility to Zika virus is mosquito genotype-dependent.

The microbiome of the mosquito Aedes aegypti is largely determined by the environment and influences mosquito susceptibility for arthropod-borne viruses (arboviruses). Larval interactions with different bacteria can have carry-over effects on adult Ae. aegypti replication of arboviruses, but little is known about the role that mosquito host genetics play in determining how larval-bacterial interactions shape Ae aegypti susceptibility to arboviruses. To address this question, we isolated single bacterial isolates and complex microbiomes from Ae. aegypti larvae from various field sites in Senegal. Either single bacterial isolates or complex microbiomes were added to two different genetic backgrounds of Ae. aegypti in a gnotobiotic larval system. Using 16S amplicon sequencing we showed that the bacterial community structure differs between the two genotypes of Ae. aegypti when given identical microbiomes, and the abundance of single bacterial taxa differed between Ae. aegypti genotypes. Using single bacterial isolates or the entire preserved complex microbiome, we tested the ability of specific larval microbiomes to drive differences in infection rates for Zika virus in different genetic backgrounds of Ae. aegypti. We observed that the proportion of Zika virus-infected adults was dependent on the interaction between the larval microbiome and Ae. aegypti host genetics. By using the larval microbiome as a component of the environment, these results demonstrate that interactions between the Ae. aegypti genotype and its environment can influence Zika virus infection. As Ae. aegypti expands and adapts to new environments under climate change, an understanding of how different genotypes interact with the same environment will be crucial for implementing arbovirus transmission control strategies.

AhR promotes phosphorylation of ARNT isoform 1 in human T cell malignancies as a switch for optimal AhR activity.

The aryl hydrocarbon receptor nuclear translocator (ARNT) is a transcription factor present in immune cells as a long and short isoform, referred to as isoforms 1 and 3, respectively. However, investigation into potential ARNT isoform­specific immune functions is lacking despite the well-established heterodimerization requirement of ARNT with, and for the activity of, the aryl hydrocarbon receptor (AhR), a critical mediator of immune homeostasis. Here, using global and targeted transcriptomics analyses, we show that the relative ARNT isoform 1:3 ratio in human T cell lymphoma cells dictates the amplitude and direction of AhR target gene regulation. Specifically, shifting the ARNT isoform 1:3 ratio lower by suppressing isoform 1 enhances, or higher by suppressing isoform 3 abrogates, AhR responsiveness to ligand activation through preprograming a cellular genetic background that directs explicit gene expression patterns. Moreover, the fluctuations in gene expression patterns that accompany a decrease or increase in the ARNT isoform 1:3 ratio are associated with inflammation or immunosuppression, respectively. Molecular studies identified the unique casein kinase 2 (CK2) phosphorylation site within isoform 1 as an essential parameter to the mechanism of ARNT isoform­specific regulation of AhR signaling. Notably, CK2-mediated phosphorylation of ARNT isoform 1 is dependent on ligand-induced AhR nuclear translocation and is required for optimal AhR target gene regulation. These observations reveal ARNT as a central modulator of AhR activity predicated on the status of the ARNT isoform ratio and suggest that ARNT-based therapies are a viable option for tuning the immune system to target immune disorders.

Establishment and comparison of human term placenta-derived trophoblast cells†.

Research on the biology of fetal-maternal barriers has been limited by access to physiologically relevant cells, including trophoblast cells. In this study, we describe the development of a human term placenta-derived cytotrophoblast immortalized cell line (hPTCCTB) derived from the basal plate. Human-term placenta-derived cytotrophoblast immortalized cell line cells are comparable to their primary cells of origin in terms of morphology, marker expression, and functional responses. We demonstrate that these can transform into syncytiotrophoblast and extravillous trophoblasts. We also compared the hPTCCTB cells to immortalized chorionic trophoblasts (hFM-CTC), trophoblasts of the chorionic plate, and BeWo cells, choriocarcinoma cell lines of conventional use. Human-term placenta-derived cytotrophoblast immortalized cell line and hFM-CTCs displayed more similarity to each other than to BeWos, but these differ in syncytialization ability. Overall, this study (1) demonstrates that the immortalized hPTCCTB generated are cells of higher physiological relevance and (2) provides a look into the distinction between the spatially distinct placental and fetal barrier trophoblasts cells, hPTCCTB and hFM-CTC, respectively.

Identification of common sequence motifs shared exclusively among selectively packed exosomal pathogenic microRNAs during rickettsial infections.

We previously reported that microRNA (miR)23a and miR30b are selectively sorted into exosomes derived from rickettsia-infected endothelial cells (R-ECExos). Yet, the mechanism remains unknown. Cases of spotted fever rickettsioses have been increasing, and infections with these bacteria cause life-threatening diseases by targeting brain and lung tissues. Therefore, the goal of the present study is to further dissect the molecular mechanism underlying R-ECExos-induced barrier dysfunction of normal recipient microvascular endothelial cells (MECs), depending on their exosomal RNA cargos. Infected ticks transmit the rickettsiae to human hosts following a bite and injections of the bacteria into the skin. In the present study, we demonstrate that treatment with R-ECExos, which were derived from spotted fever group R parkeri infected human dermal MECs, induced disruptions of the paracellular adherens junctional protein VE-cadherin, and breached the paracellular barrier function in recipient pulmonary MECs (PMECs) in an exosomal RNA-dependent manner. We did not detect different levels of miRs in parent dermal MECs following rickettsial infections. However, we demonstrated that the microvasculopathy-relevant miR23a-27a-24 cluster and miR30b are selectively enriched in R-ECExos. Bioinformatic analysis revealed that common sequence motifs are shared exclusively among the exosomal, selectively-enriched miR23a cluster and miR30b at different levels. Taken together, these data warrant further functional identification and characterization of a monopartition, bipartition, or tripartition among ACA, UCA, and CAG motifs that guide recognition of microvasculopathy-relevant miR23a-27a-24 and miR30b, and subsequently results in their selective enrichments in R-ECExos.

Viral RNA-dependent RNA polymerase mutants display an altered mutation spectrum resulting in attenuation in both mosquito and vertebrate hosts.

The presence of bottlenecks in the transmission cycle of many RNA viruses leads to a severe reduction of number of virus particles and this occurs multiple times throughout the viral transmission cycle. Viral replication is then necessary for regeneration of a diverse mutant swarm. It is now understood that any perturbation of the mutation frequency either by increasing or decreasing the accumulation of mutations in an RNA virus results in attenuation of the virus. To determine if altering the rate at which a virus accumulates mutations decreases the probability of a successful virus infection due to issues traversing host bottlenecks, a series of mutations in the RNA-dependent RNA polymerase of Venezuelan equine encephalitis virus (VEEV), strain 68U201, were tested for mutation rate changes. All RdRp mutants were attenuated in both the mosquito and vertebrate hosts, while showing no attenuation during in vitro infections. The rescued viruses containing these mutations showed some evidence of change in fidelity, but the phenotype was not sustained following passaging. However, these mutants did exhibit changes in the frequency of specific types of mutations. Using a model of mutation production, these changes were shown to decrease the number of stop codons generated during virus replication. This suggests that the observed mutant attenuation in vivo may be due to an increase in the number of unfit genomes, which may be normally selected against by the accumulation of stop codons. Lastly, the ability of these attenuated viruses to transition through a bottleneck in vivo was measured using marked virus clones. The attenuated viruses showed an overall reduction in the number of marked clones for both the mosquito and vertebrate hosts, as well as a reduced ability to overcome the known bottlenecks in the mosquito. This study demonstrates that any perturbation of the optimal mutation frequency whether through changes in fidelity or by alterations in the mutation frequency of specific nucleotides, has significant deleterious effects on the virus, especially in the presence of host bottlenecks.

Efficient identification of multiple pathways: RNA-Seq analysis of livers from 56Fe ion irradiated mice.

BACKGROUND: mRNA interaction with other mRNAs and other signaling molecules determine different biological pathways and functions. Gene co-expression network analysis methods have been widely used to identify correlation patterns between genes in various biological contexts (e.g., cancer, mouse genetics, yeast genetics). A challenge remains to identify an optimal partition of the networks where the individual modules (clusters) are neither too small to make any general inferences, nor too large to be biologically interpretable. Clustering thresholds for identification of modules are not systematically determined and depend on user-settable parameters requiring optimization. The absence of systematic threshold determination may result in suboptimal module identification and a large number of unassigned features. RESULTS: In this study, we propose a new pipeline to perform gene co-expression network analysis. The proposed pipeline employs WGCNA, a software widely used to perform different aspects of gene co-expression network analysis, and Modularity Maximization algorithm, to analyze novel RNA-Seq data to understand the effects of low-dose 56Fe ion irradiation on the formation of hepatocellular carcinoma in mice. The network results, along with experimental validation, show that using WGCNA combined with Modularity Maximization, provides a more biologically interpretable network in our dataset, than that obtainable using WGCNA alone. The proposed pipeline showed better performance than the existing clustering algorithm in WGCNA, and identified a module that was biologically validated by a mitochondrial complex I assay. CONCLUSIONS: We present a pipeline that can reduce the problem of parameter selection that occurs with the existing algorithm in WGCNA, for applicable RNA-Seq datasets. This may assist in the future discovery of novel mRNA interactions, and elucidation of their potential downstream molecular effects.

Comparative RNA-Seq transcriptome analyses reveal dynamic time-dependent effects of 56Fe, 16O, and 28Si irradiation on the induction of murine hepatocellular carcinoma.

BACKGROUND: One of the health risks posed to astronauts during deep space flights is exposure to high charge, high-energy (HZE) ions (Z > 13), which can lead to the induction of hepatocellular carcinoma (HCC). However, little is known on the molecular mechanisms of HZE irradiation-induced HCC. RESULTS: We performed comparative RNA-Seq transcriptomic analyses to assess the carcinogenic effects of 600 MeV/n 56Fe (0.2 Gy), 1 GeV/n 16O (0.2 Gy), and 350 MeV/n 28Si (0.2 Gy) ions in a mouse model for irradiation-induced HCC. C3H/HeNCrl mice were subjected to total body irradiation to simulate space environment HZE-irradiation, and liver tissues were extracted at five different time points post-irradiation to investigate the time-dependent carcinogenic response at the transcriptomic level. Our data demonstrated a clear difference in the biological effects of these HZE ions, particularly immunological, such as Acute Phase Response Signaling, B Cell Receptor Signaling, IL-8 Signaling, and ROS Production in Macrophages. Also seen in this study were novel unannotated transcripts that were significantly affected by HZE. To investigate the biological functions of these novel transcripts, we used a machine learning technique known as self-organizing maps (SOMs) to characterize the transcriptome expression profiles of 60 samples (45 HZE-irradiated, 15 non-irradiated control) from liver tissues. A handful of localized modules in the maps emerged as groups of co-regulated and co-expressed transcripts. The functional context of these modules was discovered using overrepresentation analysis. We found that these spots typically contained enriched populations of transcripts related to specific immunological molecular processes (e.g., Acute Phase Response Signaling, B Cell Receptor Signaling, IL-3 Signaling), and RNA Transcription/Expression. CONCLUSIONS: A large number of transcripts were found differentially expressed post-HZE irradiation. These results provide valuable information for uncovering the differences in molecular mechanisms underlying HZE specific induced HCC carcinogenesis. Additionally, a handful of novel differentially expressed unannotated transcripts were discovered for each HZE ion. Taken together, these findings may provide a better understanding of biological mechanisms underlying risks for HCC after HZE irradiation and may also have important implications for the discovery of potential countermeasures against and identification of biomarkers for HZE-induced HCC.

Comparative transcriptomic analysis of Rickettsia conorii during in vitro infection of human and tick host cells.

BACKGROUND: Pathogenic Rickettsia species belonging to the spotted fever group are arthropod-borne, obligate intracellular bacteria which exhibit preferential tropism for host microvascular endothelium in the mammalian hosts, resulting in disease manifestations attributed primarily to endothelial damage or dysfunction. Although rickettsiae are known to undergo evolution through genomic reduction, the mechanisms by which these pathogens regulate their transcriptome to ensure survival in tick vectors and maintenance by transovarial/transstadial transmission, in contrast to their ability to cause debilitating infections in human hosts remain unknown. In this study, we compare the expression profiles of rickettsial sRNAome/transcriptome and determine the transcriptional start sites (TSSs) of R. conorii transcripts during in vitro infection of human and tick host cells. RESULTS: We performed deep sequencing on total RNA from Amblyomma americanum AAE2 cells and human microvascular endothelial cells (HMECs) infected with R. conorii. Strand-specific RNA sequencing of R. conorii transcripts revealed the expression 32 small RNAs (Rc_sR's), which were preferentially expressed above the limit of detection during tick cell infection, and confirmed the expression of Rc_sR61, sR71, and sR74 by quantitative RT-PCR. Intriguingly, a total of 305 and 132 R. conorii coding genes were differentially upregulated (> 2-fold) in AAE2 cells and HMECs, respectively. Further, enrichment for primary transcripts by treatment with Terminator 5'-Phosphate-dependent Exonuclease resulted in the identification of 3903 and 2555 transcription start sites (TSSs), including 214 and 181 primary TSSs in R. conorii during the infection to tick and human host cells, respectively. Seventy-five coding genes exhibited different TSSs depending on the host environment. Finally, we also observed differential expression of 6S RNA during host-pathogen and vector-pathogen interactions in vitro, implicating an important role for this noncoding RNA in the regulation of rickettsial transcriptome depending on the supportive host niche. CONCLUSIONS: In sum, the findings of this study authenticate the presence of novel Rc_sR's in R. conorii, reveal the first evidence for differential expression of coding transcripts and utilization of alternate transcriptional start sites depending on the host niche, and implicate a role for 6S RNA in the regulation of coding transcriptome during tripartite host-pathogen-vector interactions.

Broom: application for non-redundant storage of high throughput sequencing data.

Motivation: The data generation capabilities of high throughput sequencing (HTS) instruments have exponentially increased over the last few years, while the cost of sequencing has dramatically decreased allowing this technology to become widely used in biomedical studies. For small labs and individual researchers, however, storage and transfer of large amounts of HTS data present a significant challenge. The recent trends in increased sequencing quality and genome coverage can be used to reconsider HTS data storage strategies. Results: We present Broom, a stand-alone application designed to select and store only high-quality sequencing reads at extremely high compression rates. Written in C++, the application accepts single and paired-end reads in FASTQ and FASTA formats and decompresses data in FASTA format. Availability and implementation: C++ code available at https://scsb.utmb.edu/labgroups/fofanov/broom.asp. Supplementary information: Supplementary data are available at Bioinformatics online.

Detection of multi-dimensional co-exclusion patterns in microbial communities.

Motivation: Identification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting micro-organisms' intolerance to each other's presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond micro-organism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network. Results: The implemented computational pipeline (CoEx) tested against 2380 microbial profiles (samples) from The Human Microbiome Project resulted in body-site specific pairwise co-exclusion patterns. Availability and implementation: C++ source code for calculation of the score and P-value for two, three and four dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https://scsb.utmb.edu/labgroups/fofanov/co-exclusion_in_microbial_communities.asp. Supplementary information: Supplementary data are available at Bioinformatics online.

Expression Profiling of Long Noncoding RNA Splice Variants in Human Microvascular Endothelial Cells: Lipopolysaccharide Effects In Vitro.

Endothelial cell interactions with lipopolysaccharide (LPS) involve both activating and repressing signals resulting in pronounced alterations in their transcriptome and proteome. Noncoding RNAs are now appreciated as posttranscriptional and translational regulators of cellular signaling and responses, but their expression status and roles during endothelial interactions with LPS are not well understood. We report on the expression profile of long noncoding (lnc) RNAs of human microvascular endothelial cells in response to LPS. We have identified a total of 10,781 and 8310 lncRNA transcripts displaying either positive or negative regulation of expression, respectively, at 3 and 24 h posttreatment. A majority of LPS-induced lncRNAs are multiexonic and distributed across the genome as evidenced by their presence on all chromosomes. Present among these are a total of 44 lncRNAs with known regulatory functions, of which 41 multiexonic lncRNAs have multiple splice variants. We have further validated splice variant-specific expression of EGO (NONHSAT087634) and HOTAIRM1 (NONHSAT119666) at 3 h and significant upregulation of lnc-IL7R at 24 h. This study illustrates the genome-wide regulation of endothelial lncRNA splice variants in response to LPS and provides a foundation for further investigations of differentially expressed lncRNA transcripts in endothelial responses to LPS and pathophysiology of sepsis/septic shock.

The ability of human nuclear DNA to cause false positive low-abundance heteroplasmy calls varies across the mitochondrial genome.

BACKGROUND: Low-abundance mutations in mitochondrial populations (mutations with minor allele frequency ≤ 1%), are associated with cancer, aging, and neurodegenerative disorders. While recent progress in high-throughput sequencing technology has significantly improved the heteroplasmy identification process, the ability of this technology to detect low-abundance mutations can be affected by the presence of similar sequences originating from nuclear DNA (nDNA). To determine to what extent nDNA can cause false positive low-abundance heteroplasmy calls, we have identified mitochondrial locations of all subsequences that are common or similar (one mismatch allowed) between nDNA and mitochondrial DNA (mtDNA). RESULTS: Performed analysis revealed up to a 25-fold variation in the lengths of longest common and longest similar (one mismatch allowed) subsequences across the mitochondrial genome. The size of the longest subsequences shared between nDNA and mtDNA in several regions of the mitochondrial genome were found to be as low as 11 bases, which not only allows using these regions to design new, very specific PCR primers, but also supports the hypothesis of the non-random introduction of mtDNA into the human nuclear DNA. CONCLUSION: Analysis of the mitochondrial locations of the subsequences shared between nDNA and mtDNA suggested that even very short (36 bases) single-end sequencing reads can be used to identify low-abundance variation in 20.4% of the mitochondrial genome. For longer (76 and 150 bases) reads, the proportion of the mitochondrial genome where nDNA presence will not interfere found to be 44.5 and 67.9%, when low-abundance mutations at 100% of locations can be identified using 417 bases long single reads. This observation suggests that the analysis of low-abundance variations in mitochondria population can be extended to a variety of large data collections such as NCBI Sequence Read Archive, European Nucleotide Archive, The Cancer Genome Atlas, and International Cancer Genome Consortium.

Bacterial small RNAs in the Genus Rickettsia.

BACKGROUND: Rickettsia species are obligate intracellular Gram-negative pathogenic bacteria and the etiologic agents of diseases such as Rocky Mountain spotted fever (RMSF), Mediterranean spotted fever, epidemic typhus, and murine typhus. Genome sequencing revealed that R. prowazekii has ~25 % non-coding DNA, the majority of which is thought to be either "junk DNA" or pseudogenes resulting from genomic reduction. These characteristics also define other Rickettsia genomes. Bacterial small RNAs, whose biogenesis is predominantly attributed to either the intergenic regions (trans-acting) or to the antisense strand of an open reading frame (cis-acting), are now appreciated to be among the most important post-transcriptional regulators of bacterial virulence and growth. We hypothesize that intergenic regions in rickettsial species encode for small, non-coding RNAs (sRNAs) involved in the regulation of its transcriptome, leading to altered virulence and adaptation depending on the host niche. RESULTS: We employed a combination of bioinformatics and in vitro approaches to explore the presence of sRNAs in a number of species within Genus Rickettsia. Using the sRNA Identification Protocol using High-throughput Technology (SIPHT) web interface, we predicted over 1,700 small RNAs present in the intergenic regions of 16 different strains representing 13 rickettsial species. We further characterized novel sRNAs from typhus (R. prowazekii and R. typhi) and spotted fever (R. rickettsii and R. conorii) groups for their promoters and Rho-independent terminators using Bacterial Promoter Prediction Program (BPROM) and TransTermHP prediction algorithms, respectively. Strong σ70 promoters were predicted upstream of all novel small RNAs, indicating the potential for transcriptional activity. Next, we infected human microvascular endothelial cells (HMECs) with R. prowazekii for 3 h and 24 h and performed Next Generation Sequencing to experimentally validate the expression of 26 sRNA candidates predicted in R. prowazekii. Reverse transcriptase PCR was also used to further verify the expression of six putative novel sRNA candidates in R. prowazekii. CONCLUSIONS: Our results yield clear evidence for the expression of novel R. prowazekii sRNA candidates during infection of HMECs. This is the first description of novel small RNAs for a highly pathogenic species of Rickettsia, which should lead to new insights into rickettsial virulence and adaptation mechanisms.

Regional trends in diagnosis of advanced lung cancer in Michigan over 33 years.

Background: Lung cancer is the most common cancer killer worldwide. Nearly 80 percent of lung cancers are diagnosed at advanced stages. Lack of access to medical care and undwerutilized lung cancer screening are key reasons for advanced diagnoses. We sought to understand the regional differences in presentation of lung cancer across Michigan. Utilizing a comprehensive cancer registry over 33 years, our goal was to examine associations between sociodemographic patient factors and diagnoses at advanced stages. Methods: The Michigan Cancer Registry was queried from 1985 to 2018 to include all new diagnoses of non-small cell lung cancer (NSCLC) using International Classification of Diseases for Oncology (ICD-O) version 3 codes. NSCLC was categorized as early, regional and distant disease. Advanced disease was considered to be any disease that was regional or distant. NSCLC rates were calculated and mapped at the zip code level using the 2010 population as the denominator and spatial empirical Bayes methodology. Regional hospital service areas were constructed using travel time to treatment from the patient's zip code centroid. Logistic regression models were estimated to investigate the significance of rural vs. urban and travel time on level of disease at presentation. Kaplan-Meier and multivariate survival analysis was performed to evaluate the association between distance from the nearest medical center and length of survival controlling for known risk factors for lung cancer. Results: From 1985 to 2018, there were 141,977 patients in Michigan diagnosed with NSCLC. In 1985, men were 2.2 times more likely than women to be diagnosed but by 2018 women and men developed disease at equal rates. Mean age was 67.8 years. Among all patients with known stage of disease, 72.5% of patients were diagnosed with advanced disease. Regional and distant NSCLC rates were both higher in the northern parts of the state. Longer drive times in rural regions also significantly increased the likelihood of advanced NSCLC diagnoses, in particular regional lung cancer. Patients with longer drive times also experienced overall worse survival after controlling for other factors. Conclusions: Regional disparities exist in Michigan for diagnoses of NSCLC at advanced stages. Factors such as lack of screening in urban regions and distances to treating institutions in rural areas likely contribute to the increased likelihood of advanced NSCLC. Future interventions should target the specific needs of residents to detect disease at earlier stages and improve overall outcomes.

Microbial metabolite butyrate modulates granzyme B in tolerogenic IL-10 producing Th1 cells to regulate intestinal inflammation.

CD4+ T cells play a critical role in regulating autoimmune diseases, and intestinal microbial metabolites control various immune responses. Granzyme B (GzmB)-producing CD4+ T cells have been recently reported to participate in the pathogenesis of autoimmune diseases. Here, we found that GzmbB-deficient CD4+ T cells induced more severe colitis in Rag1-/- mice than wild-type (WT) CD4+ T cells. Germ-free (GF) mice exhibited a lower expression of GzmB in intestinal CD4+ T cells compared to specific pathogen-free (SPF) mice. Intestinal microbial metabolite butyrate increased GzmB expression in CD4+ T cells, especially in IL-10-producing Th1 cells, through HDAC inhibition and GPR43, but not GPR41 and GPR109a. Butyrate-treated GzmB-deficient CD4+ T cells demonstrated more severe colitis compared to butyrate-treated WT CD4+ T cells in the T cell transfer model. Butyrate altered intestinal microbiota composition, but altered microbiota did not mediate butyrate induction of intestinal CD4+ T cell expression of GzmB in mice. Blimp1 was involved in the butyrate induction of GzmB in IL-10-producing Th1 cells. Glucose metabolism, including glycolysis and pyruvate oxidation, mediated butyrate induction of GzmB in Th1 cells. In addition, we found that IKZF3 and NR2F6 regulated GzmB expression induced by butyrate. Together, our studies underscored the critical role of GzmB in mediating gut bacterial metabolite butyrate regulation of T cell tolerance at the mucosal surface.

Autophagy Determines Distinct Cell Fates in Human Amnion and Chorion Cells.

Human fetal membranes (amniochorion) that line the intrauterine cavity consist of two distinct cell layers; single-layer amnion epithelial cells (AEC) and multilayer chorion trophoblast cells (CTC). These layers are connected through a collagen-rich extracellular matrix. Cellular remodeling helps support membrane growth and integrity during gestation and helps to maintain pregnancy. Preterm prelabor rupture of the human amniochorionic (fetal) membrane (pPROM) is antecedent to 40% of all spontaneous preterm birth. Oxidative stress (OS) induced activation of the p38 MAPK due to various maternal risk exposures and the amniochorion cells' senescence are reported pathological features of pPROM. Our transcriptomics analysis implicated dysregulated autophagy and epithelial-mesenchymal transition (EMT) in fetal membranes from pPROM. The molecular interplay between OS-induced p38 MAPK activation, autophagy, and EMT was investigated in AECs and CTCs to better understand the involvement of autophagy and EMT. We report the differential impact of OS on the autophagic machinery in AECs and CTCs, resulting in distinct cell fates. In AECs, OS-induced p38 MAPK activation causes autophagosome accumulation and reduced autophagic flux mediated by decreased ULK1 activity and kinase activity, leading to senescence. In CTCs, induction of autophagy has a limited effect; however, inhibition of autophagy led to SQSTM1-mediated EMT of trophoblast cells. Autophagy, EMT, and senescence were associated with proinflammatory changes. Thus, AECs and CTCs respond differently to OS via differential autophagy response, partly mediated via p38 MAPK. Besides senescence, OS-induced autophagy dysregulation in amniochorion cells may play a mechanistic role in pPROM pathophysiology.

Interkingdom interactions shape the fungal microbiome of mosquitoes.

BACKGROUND: The mosquito microbiome is an important modulator of vector competence and vectoral capacity. Unlike the extensively studied bacterial microbiome, fungal communities in the mosquito microbiome (the mycobiome) remain largely unexplored. To work towards getting an improved understanding of the fungi associated with mosquitoes, we sequenced the mycobiome of three field-collected and laboratory-reared mosquito species (Aedes albopictus, Aedes aegypti, and Culex quinquefasciatus). RESULTS: Our analysis showed both environment and host species were contributing to the diversity of the fungal microbiome of mosquitoes. When comparing species, Ae. albopictus possessed a higher number of diverse fungal taxa than Cx. quinquefasciatus, while strikingly less than 1% of reads from Ae. aegypti samples were fungal. Fungal reads from Ae. aegypti were < 1% even after inhibiting host amplification using a PNA blocker, indicating that this species lacked a significant fungal microbiome that was amplified using this sequencing approach. Using a mono-association mosquito infection model, we confirmed that mosquito-derived fungal isolates colonize Aedes mosquitoes and support growth and development at comparable rates to their bacterial counterparts. Strikingly, native bacterial taxa isolated from mosquitoes impeded the colonization of symbiotic fungi in Ae. aegypti suggesting interkingdom interactions shape fungal microbiome communities. CONCLUSION: Collectively, this study adds to our understanding of the fungal microbiome of different mosquito species, that these fungal microbes support growth and development, and highlights that microbial interactions underpin fungal colonization of these medically relevent species.

Exclusive Enteral Nutrition Beneficially Modulates Gut Microbiome in a Preclinical Model of Crohn's-like Colitis.

Exclusive enteral nutrition (EEN) is an established dietary treatment for Crohn's disease (CD) by alleviating inflammation and inducing remission. However, the mechanisms of action of EEN are incompletely understood. As CD is associated with gut microbiome dysbiosis, we investigated the effect of EEN on the microbiome in a rat model of CD-like colitis. The rat model of CD-like colitis was established by an intracolonic instillation of TNBS at 65 mg/kg in 250 µL of 40% ethanol. Sham control rats were instilled with saline. Rats were fed ad libitum with either regular pellet food or EEN treatment with a clear liquid diet (Ensure). Rats were euthanized at 7 days. Fecal pellets were collected from the distal colon for 16S rRNA sequencing analysis of gut microbiota. In addition, colon tissues were taken for histological and molecular analyses in all the groups of rats. EEN administration to TNBS-induced CD rats significantly improved the body weight change, inflammation scores, and disease activity index. The mRNA expression of IL-17A and interferon-γ was significantly increased in the colonic tissue in TNBS rats when fed with regular food. However, EEN treatment significantly attenuated the increase in IL-17A and interferon-γ in TNBS rats. Our 16S rRNA sequencing analysis found that gut microbiota diversity and compositions were significantly altered in TNBS rats, compared to controls. However, EEN treatment improved alpha diversity and increased certain beneficial bacteria such as Lactobacillus and Dubosiella and decreased bacteria such as Bacteroides and Enterorhabdus in CD-like rats, compared to CD-like rats with the regular pellet diet. In conclusion, EEN treatment increases the diversity of gut microbiota and the composition of certain beneficial bacteria. These effects may contribute to the reduced inflammation by EEN in the rat model of CD-like colitis.

Identification of multivariable Boolean patterns in microbiome and microbial gene composition data.

Virtually every biological system is governed by complex relations among its components. Identifying such relations requires a rigorous or heuristics-based search for patterns among variables/features of a system. Various algorithms have been developed to identify two-dimensional (involving two variables) patterns employing correlation, covariation, mutual information, etc. It seems obvious, however, that comprehensive descriptions of complex biological systems need also to include more complicated multivariable relations, which can only be described using patterns that simultaneously embrace 3, 4, and more variables. The goal of this manuscript is to (a) introduce a novel type of associations (multivariable Boolean patterns) that can be manifested between features of complex systems but cannot be identified (described) by traditional pair-vise metrics; (b) propose patterns classification method, and (c) provide a novel definition of the pattern's strength (pattern's score) able to accommodate heterogeneous multi-omics data. To demonstrate the presence of such patterns, we performed a search for all possible 2-, 3-, and 4-dimensional patterns in historical data from the Human Microbiome Project (15 body sites) and collection of H. pylori genomes associated with gastric ulcers, gastritis, and duodenal ulcers. In all datasets under consideration, we were able to identify hundreds of statistically significant multivariable patterns. These results suggest that such patterns can be common in microbial genomics/microbiomics systems.

The relationship of social determinants and distress in newly diagnosed cancer patients.

Patients with a new cancer diagnosis can experience distress when diagnosed. There are disparities in treatment of cancer patients based on social determinants, but minimal research exists on the relationship of those social determinants and distress after a new cancer diagnosis. Our goals were to determine the social determinants associated with distress after a new cancer diagnosis and determine the relationship of distress with outcome. Patients with a new cancer diagnosis at one institution from January 2019 to December 2020 were analyzed. Patients were given the National Comprehensive Cancer Network (NCCN) distress thermometer during their first visit. Demographics, tumor characteristics, clinical variables and survival were recorded. Patients were also asked to share specific factors that led to distress, including: (1) financial, (2) transportation, (3) childcare and (4) religious. A total of 916 patients returned distress thermometers. Mean age was 59.1 years. Females comprised 71.3 (653/916) percent of the cohort. On Dunn's multiple comparison, the following factors were associated with increased distress level: female (p < 0.01), ages 27 to 45 (p < 0.01), uninsured (p < 0.01) and unemployed (p < 0.01). Patients with higher distress scores also experienced worse overall survival (p < 0.05). Females, young patients, uninsured patients and unemployed patients experience more distress after a new cancer diagnosis. Increased distress is independently associated with worse overall survival. Social determinants can be used to predict which patients may require focused interventions to reduce distress after a new cancer diagnosis.