Transcriptome analysis of six tissues obtained post-mortem from sepsis patients.

Septic shock is a life-threatening clinical condition characterized by a robust immune inflammatory response to disseminated infection. Little is known about its impact on the transcriptome of distinct human tissues. To address this, we performed RNA sequencing of samples from the prefrontal cortex, hippocampus, heart, lung, kidney and colon of seven individuals who succumbed to sepsis and seven uninfected controls. We identified that the lungs and colon were the most affected organs. While gene activation dominated, strong inhibitory signals were also detected, particularly in the lungs. We found that septic shock is an extremely heterogeneous disease, not only when different individuals are investigated, but also when comparing different tissues of the same patient. However, several pathways, such as respiratory electron transport and other metabolic functions, revealed distinctive alterations, providing evidence that tissue specificity is a hallmark of sepsis. Strikingly, we found evident signals of accelerated ageing in our sepsis population.

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions.

Pathogens can cause a wide variety of infectious diseases. The biological processes induced by the host in response to infection determine the severity of the disease. To study such processes, researchers can use high-throughput sequencing techniques (RNA-seq) that measure the dynamic changes of the host transcriptome at different stages of infection, clinical outcomes, or disease severity.This investigation can lead to a better understanding of the diseases, as well as uncovering potential drug targets and treatments. The protocol presented here describes a complete pipeline to analyze RNA-sequencing data from raw reads to functional analysis. The pipeline is divided into five steps: (1) quality control of the data; (2) mapping and annotation of genes; (3) statistical analysis to identify differentially expressed genes and co-expressed genes; (4) determination of the molecular degree of the perturbation of samples; and (5) functional analysis. Step 1 removes technical artifacts that may impact the quality of downstream analyses. In step 2, genes are mapped and annotated according to standard library protocols. The statistical analysis in step 3 identifies genes that are differentially expressed or co-expressed in infected samples, in comparison with non-infected ones. Sample variability and the presence of potential biological outliers are verified using the molecular degree of perturbation approach in step 4. Finally, the functional analysis in step 5 reveals the pathways associated with the disease phenotype. The presented pipeline aims to support researchers through the RNA-seq data analysis from host-pathogen interaction studies and drive future in vitro or in vivo experiments, that are essential to understand the molecular mechanism of infections.

Systems analysis of subjects acutely infected with the Chikungunya virus.

The largest ever recorded epidemic of the Chikungunya virus (CHIKV) broke out in 2004 and affected four continents. Acute symptomatic infections are typically associated with the onset of fever and often debilitating polyarthralgia/polyarthritis. In this study, a systems biology approach was adopted to analyze the blood transcriptomes of adults acutely infected with the CHIKV. Gene signatures that were associated with viral RNA levels and the onset of symptoms were identified. Among these genes, the putative role of the Eukaryotic Initiation Factor (eIF) family genes and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC3A) in the CHIKV replication process were displayed. We further compared these signatures with signatures induced by the Dengue virus infection and rheumatoid arthritis. Finally, we demonstrated that the CHIKV in vitro infection of murine bone marrow-derived macrophages induced IL-1 beta production in a mechanism that is significantly dependent on the inflammasome NLRP3 activation. The observations provided valuable insights into virus-host interactions during the acute phase and can be instrumental in the investigation of new and effective therapeutic interventions.

Systems analysis of subjects acutely infected with the Chikungunya virus

The largest ever recorded epidemic of the Chikungunya virus (CHIKV) broke out in 2004 and affected four continents. Acute symptomatic infections are typically associated with the onset of fever and often debilitating polyarthralgia/polyarthritis. In this study, a systems biology approach was adopted to analyze the blood transcriptomes of adults acutely infected with the CHIKV. Gene signatures that were associated with viral RNA levels and the onset of symptoms were identified. Among these genes, the putative role of the Eukaryotic Initiation Factor (eIF) family genes and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC3A) in the CHIKV replication process were displayed. We further compared these signatures with signatures induced by the Dengue virus infection and rheumatoid arthritis. Finally, we demonstrated that the CHIKV in vitro infection of murine bone marrow-derived macrophages induced IL-1 beta production in a mechanism that is significantly dependent on the inflammasome NLRP3 activation. The observations provided valuable insights into virus-host interactions during the acute phase and can be instrumental in the investigation of new and effective therapeutic interventions.

Systems analysis of subjects acutely infected with the Chikungunya virus

The largest ever recorded epidemic of the Chikungunya virus (CHIKV) broke out in 2004 and affected four continents. Acute symptomatic infections are typically associated with the onset of fever and often debilitating polyarthralgia/polyarthritis. In this study, a systems biology approach was adopted to analyze the blood transcriptomes of adults acutely infected with the CHIKV. Gene signatures that were associated with viral RNA levels and the onset of symptoms were identified. Among these genes, the putative role of the Eukaryotic Initiation Factor (eIF) family genes and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC3A) in the CHIKV replication process were displayed. We further compared these signatures with signatures induced by the Dengue virus infection and rheumatoid arthritis. Finally, we demonstrated that the CHIKV in vitro infection of murine bone marrow-derived macrophages induced IL-1 beta production in a mechanism that is significantly dependent on the inflammasome NLRP3 activation. The observations provided valuable insights into virus-host interactions during the acute phase and can be instrumental in the investigation of new and effective therapeutic interventions.

miR-181a-5p Regulates TNF-α and miR-21a-5p Influences Gualynate-Binding Protein 5 and IL-10 Expression in Macrophages Affecting Host Control of Brucella abortus Infection.

Brucella abortus is a Gram-negative intracellular bacterium that causes a worldwide zoonosis termed brucellosis, which is characterized as a debilitating infection with serious clinical manifestations leading to severe complications. In spite of great advances in studies involving host-B. abortus interactions, there are many gaps related to B. abortus modulation of the host immune response through regulatory mechanisms. Here, we deep sequenced small RNAs from bone marrow-derived macrophages infected with B. abortus, identifying 69 microRNAs (miRNAs) that were differentially expressed during infection. We further validated the expression of four upregulated and five downregulated miRNAs during infection in vitro that displayed the same profile in spleens from infected mice at 1, 3, or 6 days post-infection. Among these miRNAs, mmu-miR-181a-5p (upregulated) or mmu-miR-21a-5p (downregulated) were selected for further analysis. First, we determined that changes in the expression of both miRNAs induced by infection were dependent on the adaptor molecule MyD88. Furthermore, evaluating putative targets of mmu-miR-181a-5p, we demonstrated this miRNA negatively regulates TNF-α expression following Brucella infection. By contrast, miR-21a-5p targets included a negative regulator of IL-10, programmed cell death protein 4, and several guanylate-binding proteins (GBPs). As a result, during infection, miR-21a-5p led to upregulation of IL-10 expression and downregulation of GBP5 in macrophages infected with Brucella. Since GBP5 and IL-10 are important molecules involved in host control of Brucella infection, we decided to investigate the role of mmu-miR-21a-5p in bacterial replication in macrophages. We observed that treating macrophages with a mmu-miR-21a-5p mimic enhanced bacterial growth, whereas transfection of its inhibitor reduced Brucella load in macrophages. Taken together, the results indicate that downregulation of mmu-miR-21a-5p induced by infection increases GBP5 levels and decreases IL-10 expression thus contributing to bacterial control in host cells.

The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis.

BACKGROUND: Dengue is a vector-borne disease caused by the dengue virus (DENV). Despite the crucial role of Aedes mosquitoes in DENV transmission, pure vector indices poorly correlate with human infections. Therefore there is great need for a better understanding of the spatial and temporal scales of DENV transmission between mosquitoes and humans. Here, we have systematically monitored the circulation of DENV in individual Aedes spp. mosquitoes and human patients from Caratinga, a dengue endemic city in the state of Minas Gerais, in Southeast Brazil. From these data, we have developed a novel stochastic point process pattern algorithm to identify the spatial and temporal association between DENV infected mosquitoes and human patients. METHODS: The algorithm comprises of: (i) parameterization of the variogram for the incidence of each DENV serotype in mosquitoes; (ii) identification of the spatial and temporal ranges and variances of DENV incidence in mosquitoes in the proximity of humans infected with dengue; and (iii) analysis of the association between a set of environmental variables and DENV incidence in mosquitoes in the proximity of humans infected with dengue using a spatio-temporal additive, geostatistical linear model. RESULTS: DENV serotypes 1 and 3 were the most common virus serotypes detected in both mosquitoes and humans. Using the data on each virus serotype separately, our spatio-temporal analyses indicated that infected humans were located in areas with the highest DENV incidence in mosquitoes, when incidence is calculated within 2.5-3 km and 50 days (credible interval 30-70 days) before onset of symptoms in humans. These measurements are in agreement with expected distances covered by mosquitoes and humans and the time for virus incubation. Finally, DENV incidence in mosquitoes found in the vicinity of infected humans correlated well with the low wind speed, higher air temperature and northerly winds that were more likely to favor vector survival and dispersal in Caratinga. CONCLUSIONS: We have proposed a new way of modeling bivariate point pattern on the transmission of arthropod-borne pathogens between vector and host when the location of infection in the latter is known. This strategy avoids some of the strong and unrealistic assumptions made by other point-process models. Regarding virus transmission in Caratinga, our model showed a strong and significant association between high DENV incidence in mosquitoes and the onset of symptoms in humans at specific spatial and temporal windows. Together, our results indicate that vector surveillance must be a priority for dengue control. Nevertheless, localized vector control at distances lower than 2.5 km around premises with infected vectors in densely populated areas are not likely to be effective.

Viral RNA recognition by the Drosophila small interfering RNA pathway.

Viral RNA is a common activator of antiviral responses. In this review, we dissect the mechanism of viral RNA recognition by the small interfering RNA pathway in Drosophila melanogaster. This antiviral response in fruit flies can help understand general principles of nucleic acid recognition.

MiRNA expression profile for the human gastric antrum region using ultra-deep sequencing.

BACKGROUND: MicroRNAs are small non-coding nucleotide sequences that regulate gene expression. These structures are fundamental to several biological processes, including cell proliferation, development, differentiation and apoptosis. Identifying the expression profile of microRNAs in healthy human gastric antrum mucosa may help elucidate the miRNA regulatory mechanisms of the human stomach. METHODOLOGY/PRINCIPAL FINDINGS: A small RNA library of stomach antrum tissue was sequenced using high-throughput SOLiD sequencing technology. The total read count for the gastric mucosa antrum region was greater than 618,000. After filtering and aligning using with MirBase, 148 mature miRNAs were identified in the gastric antrum tissue, totaling 3,181 quality reads; 63.5% (2,021) of the reads were concentrated in the eight most highly expressed miRNAs (hsa-mir-145, hsa-mir-29a, hsa-mir-29c, hsa-mir-21, hsa-mir-451a, hsa-mir-192, hsa-mir-191 and hsa-mir-148a). RT-PCR validated the expression profiles of seven of these highly expressed miRNAs and confirmed the sequencing results obtained using the SOLiD platform. CONCLUSIONS/SIGNIFICANCE: In comparison with other tissues, the antrum's expression profile was unique with respect to the most highly expressed miRNAs, suggesting that this expression profile is specific to stomach antrum tissue. The current study provides a starting point for a more comprehensive understanding of the role of miRNAs in the regulation of the molecular processes of the human stomach.