Circulating miRNome of Trachemys scripta after elective gonadectomy under general anesthesia

Post-surgical management is an important issue in veterinary medicine, requiring biomarkers with high sensitivity and specificity for timely and effective treatment. Emerging evidence suggests that miRNAs are promising stress- and pain-related markers. The aims were to profile the circulating miRNA signature in plasma of turtles (Trachemysscripta) and point out potential candidate biomarkers to assess the status of the animal. The plasma of female turtles underwent surgical gonadectomy were collected 24 h pre-surgery, and 2.5 h and 36 h post-surgery. The expression of miRNAs was profiled by Next Generation Sequencing and the dysregulated miRNAs were validated using RT-qPCR. The diagnostic value of miRNAs was calculated by ROC curves. The results showed that 14 miRNAs were differentially expressed over time. RT-qPCR validation highlighted that 2-miR-499-3p and miR-203-5p-out of 8 miRNAs tested were effectively modulated. The Area Under the Curve (AUC) of miR-203-5p was fair (AUC 0.7934) in discriminating pre- and 36 h post-surgery samples and poor for other time points; the AUC of miR-499-3p was excellent (AUC 0.944) in discriminating pre-surgery and 2.5 h post-surgery samples, and fair in discriminating pre-surgery and 36 h post-surgery (AUC 0.7292) and 2.5 h and 36 h post-surgery (AUC 0.7569) samples. In conclusion, we demonstrated for the first time that miRNAs profile changes in plasma of turtles underwent surgical oophorectomy and identified miR-203-5p and miR-499-3p as potential candidate biomarkers to assess animals' status. Further studies are necessary to confirm their diagnostic value and to investigate functional and mechanistic networks to improve our understanding of the biological processes.

Evaluating and Correcting Inherent Bias of microRNA Expression in Illumina Sequencing Analysis

microRNA (miRNA) expression profiles based on the highly powerful Illumina sequencing technology rely on the construction of cDNA libraries in which adaptor ligation is known to deeply favor some miRNAs over others. This introduces erroneous measurements of the miRNA abundances and relative miRNA quantities in biological samples. Here, by using the commercial miRXplore Universal Reference that contains an equimolar mixture of 963 animal miRNAs and TruSeq or bulged adaptors, we describe a method for correcting ligation biases in expression profiles obtained with standard protocols of cDNA library construction and provide data for quantifying the true miRNA abundances in biological samples. Ligation biases were evaluated at three ratios of miRNA to 3′-adaptor and four numbers of polymerase chain reaction amplification cycles by calculating efficiency captures/correcting factors for each miRNA. We show that ligation biases lead to over- or under-expression covering a 10⁵ amplitude range. We also show that, at each miRNA:3′-adaptor ratio, coefficients of variation (CVs) of efficiency captures calculated over the four number of amplification cycles using sliding windows of 10 values ranged from 0.1 for the miRNAs of high expression to 0.6 for the miRNAs of low expression. Efficiency captures of miRNAs of high and low expression in profiles are therefore differently impacted by the number of amplification cycles. Importantly, we observed that at a given number of amplification cycles, CVs of efficiency captures calculated over the three miRNA:3′-adaptor ratios displayed a steady value of 0.3 +/− 0.05 STD for miRNAs of high and low expression. This allows, at a given number of amplification cycles, accurate comparison of miRNA expression between biological samples over a substantial expression range. Finally we provide tables of correcting factors that allow to measure the abundances of 963 miRNAs in biological samples from TruSeq-based expression profiles and, an example of their use by characterizing miRNAs of the let-7, miR-26, miR-29, and miR-30 families as the more abundant miRNAs of the rat adult cerebellum.

Characterization of circulating miRNA signature in water buffaloes (Bubalus bubalis) during Brucella abortus infection and evaluation as potential biomarkers for non-invasive diagnosis in vaginal fluid

Brucellosis is an infectious disease caused by bacteria from the Brucella genus that can be transmitted to humans through contact with infected animals or contaminated animal products. Brucellosis also causes financial losses in animal production. Ruminants are highly susceptible to brucellosis, and the causative agent water buffaloes (Bubalus bubalis) is Brucella abortus. Circulating microRNAs (miRNAs) are cropping up as promising biomarkers for several infectious diseases. The goals of this study were to characterize the serum miRNA signature associated with brucellosis in water buffaloes and investigate the miRNAs’ potential use as biomarkers in vaginal fluids. Next Generation Sequencing was used to assess miRNA expression profiles in Brucella-positive and Brucella-negative blood sera; dysregulated miRNAs in blood serum and vaginal fluids were validated using RT-qPCR. ROC curves were generated to evaluate the diagnostic value of miRNAs for Brucella. GO and KEGG pathway enrichment analyses were exploited to investigate the biological functions of dysregulated miRNAs. The results showed that 20 miRNAs were modulated, of which, 12 were upregulated and 8 were downregulated. These findings were corroborated by RT-qPCR, and ROC curves indicated that the miRNAs can serve as potential biomarkers for Brucella. GO and KEGG pathway analyses pointed out that some of these miRNAs are related to immune response and apoptosis. These results provided an overview of miRNA expression profiles and highlighted potential biomarkers for Brucella infection in water buffaloes. We also demonstrated the potential of vaginal fluids in studies involving microRNA detection. Further functional and mechanistic studies of these miRNAs may improve our understanding of the biological processes involved in Brucella infection and host immune response.

Extensive screening of microRNA populations identifies hsa-miR-375 and hsa-miR-133a-3p as selective markers for human rectal and colon cancer

MicroRNAs (miRNAs) are ∼22-nt molecules exerting control of protein expression in cancer tissues. The current study determined the full spectrum of miRNA dysregulation in freshly isolated human colon or rectal cancer biopsies as well as in controls of healthy adjacent tissue (total of n = 100) using an Illumina sequencing technology. In this work, we aimed to identify miRNAs that may serve as future marker to discern between these two subtypes. DESeq2 analysis revealed 53 significantly dysregulated miRNAs in colon cancer, 67 miRNAs in rectal cancer, and 97 miRNAs in both at a P_adj value < 0.05 and ≥ 10 read counts. 65% of miRNAs were upregulated in colon as well as rectal cancer. Highest significant dysregulation (P_adj < 0.00001) was detected for hsa-miR-21-5p, -215-5p and -378a in both colon and rectal cancer. Among the group of miRNAs with P_adj < 0.05 and more than 2-fold expression differences, hsa-miR-375 was detected in rectal cancer only, and hsa-miR-133a-3p only in colon cancer. Receiver operating characteristic (ROC) analysis confirmed highly distinct sensitivities for hsa-miR-375 to detect rectal cancer (area under the curve (AUC): 0.9), while hsa-miR-133a-3p (AUC: 0.89) had the highest sensitivity for detecting colon cancer. We conclude that hsa-miR-375 and hsa-miR-133a-3p may serve as new markers of rectal or colon cancer and should be further investigated to search for different etiologies of colorectal cancer.

miRNA Long-Term Response to Early Metabolic Environmental Challenge in Hypothalamic Arcuate Nucleus

Epidemiological reports and studies using rodent models indicate that early exposure to nutrient and/or hormonal challenges can reprogram metabolism at adulthood. Hypothalamic arcuate nucleus (ARC) integrates peripheral and central signals to adequately regulate energy homeostasis. microRNAs (miRNAs) participate in the control of gene expression of large regulatory networks including many signaling pathways involved in epigenetics regulations. Here, we have characterized and compared the miRNA population of ARC of adult male rats continuously exposed to a balanced metabolic environment to the one of adult male rats exposed to an unbalanced high-fat/high-carbohydrate/moderate-protein metabolic environment during the perinatal period and/or at adulthood that consequently displayed hyperinsulinemia and/or hyperleptinemia. We identified more than 400 miRNA species in ARC of adult male rats. By comparing the miRNA content of six biological replicates in each of the four perinatal/adult environments/rat groups, we identified the 10 miRNAs specified by clusters miR-96/182/183, miR-141/200c, and miR-200a/200b/429 as miRNAs of systematic and uncommonly high variation of expression. This uncommon variation of expression may underlie high individual differences in aging disease susceptibilities. By comparing the miRNA content of the adult ARC between the rat groups, we showed that the miRNA population was not affected by the unbalanced adult environment while, in contrast, the expression of 11 miRNAs was repeatedly impacted by the perinatal unbalanced environment. Our data revealed a miRNA response of adult ARC to early metabolic environmental challenge.

Circulating microRNAs as Potential Biomarkers of Infectious Disease

microRNAs (miRNAs) are a class of small non-coding endogenous RNA molecules that regulate a wide range of biological processes by post-transcriptionally regulating gene expression. Thousands of these molecules have been discovered to date, and multiple miRNAs have been shown to coordinately fine-tune cellular processes key to organismal development, homeostasis, neurobiology, immunobiology, and control of infection. The fundamental regulatory role of miRNAs in a variety of biological processes suggests that differential expression of these transcripts may be exploited as a novel source of molecular biomarkers for many different disease pathologies or abnormalities. This has been emphasized by the recent discovery of remarkably stable miRNAs in mammalian biofluids, which may originate from intracellular processes elsewhere in the body. The potential of circulating miRNAs as biomarkers of disease has mainly been demonstrated for various types of cancer. More recently, however, attention has focused on the use of circulating miRNAs as diagnostic/prognostic biomarkers of infectious disease; for example, human tuberculosis caused by infection with Mycobacterium tuberculosis, sepsis caused by multiple infectious agents, and viral hepatitis. Here, we review these developments and discuss prospects and challenges for translating circulating miRNA into novel diagnostics for infectious disease.

Holistic and Affordable Analyses of MicroRNA Expression Profiles Using Tagged cDNA Libraries and a Multiplex Sequencing Strategy

Small and long noncoding RNAs (ncRNAs) are key regulators of gene expression. Variations in ncRNA expression patterns can consequently affect the control of many cellular processes. Not just since 2006, when Andrew Z Fire and Craig C Mello were jointly awarded The Nobel Prize in Physiology or Medicine for their discovery of RNA interference, great efforts were undertaken to unleash the biomedical applicability of small noncoding RNAs, in particular microRNAs. With the technological evolution of massive parallel sequencing technologies over the last years, which now are available for an increasing number of scientists, there is a demand for comprehensible and efficient workflows reliable even for unique and valuable clinical specimens. Here we describe a highly reproducible low-cost protocol for analyses of miRNA expression patterns using tagged cDNA libraries and a multiplex sequencing strategy following an Illumina-like protocol. This protocol easily allows the identification of expression differences from samples of tissues of 1-2 mm³ and fluids of 50-200 μL. We further provide entry points into useful computational biology applications, whose target groups explicitly involve non-bioinformaticians.