Oocyte quality is enhanced by hypoglycosylated FSH through increased cell-to-cell interaction during mouse follicle development.

Macroheterogeneity in follicle-stimulating hormone (FSH) ß-subunit N-glycosylation results in distinct FSH glycoforms. Hypoglycosylated FSH21 is the abundant and more bioactive form in pituitaries of females under 35 years of age, whereas fully glycosylated FSH24 is less bioactive and increases with age. To investigate whether the shift in FSH glycoform abundance contributes to the age-dependent decline in oocyte quality, the direct effects of FSH glycoforms on folliculogenesis and oocyte quality were determined using an encapsulated in vitro mouse follicle growth system. Long-term culture (10-12 days) with FSH21 (10 ng/ml) enhanced follicle growth, estradiol secretion and oocyte quality compared with FSH24 (10 ng/ml) treatment. FSH21 enhanced establishment of transzonal projections, gap junctions and cell-to-cell communication within 24 h in culture. Transient inhibition of FSH21-mediated bidirectional communication abrogated the positive effects of FSH21 on follicle growth, estradiol secretion and oocyte quality. Our data indicate that FSH21 promotes folliculogenesis and oocyte quality in vitro by increasing cell-to-cell communication early in folliculogenesis, and that the shift in in vivo abundance from FSH21 to FSH24 with reproductive aging may contribute to the age-dependent decline in oocyte quality.

The single-cell opioid responses in the context of HIV (SCORCH) consortium.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

The mutational landscape of a US Midwestern breast cancer cohort reveals subtype-specific cancer drivers and prognostic markers.

BACKGROUND: Female breast cancer remains the second leading cause of cancer-related death in the USA. The heterogeneity in the tumor morphology across the cohort and within patients can lead to unpredictable therapy resistance, metastasis, and clinical outcome. Hence, supplementing classic pathological markers with intrinsic tumor molecular markers can help identify novel molecular subtypes and the discovery of actionable biomarkers. METHODS: We conducted a large multi-institutional genomic analysis of paired normal and tumor samples from breast cancer patients to profile the complex genomic architecture of breast tumors. Long-term patient follow-up, therapeutic regimens, and treatment response for this cohort are documented using the Breast Cancer Collaborative Registry. The majority of the patients in this study were at tumor stage 1 (51.4%) and stage 2 (36.3%) at the time of diagnosis. Whole-exome sequencing data from 554 patients were used for mutational profiling and identifying cancer drivers. RESULTS: We identified 54 tumors having at least 1000 mutations and 185 tumors with less than 100 mutations. Tumor mutational burden varied across the classified subtypes, and the top ten mutated genes include MUC4, MUC16, PIK3CA, TTN, TP53, NBPF10, NBPF1, CDC27, AHNAK2, and MUC2. Patients were classified based on seven biological and tumor-specific parameters, including grade, stage, hormone receptor status, histological subtype, Ki67 expression, lymph node status, race, and mutational profiles compared across different subtypes. Mutual exclusion of mutations in PIK3CA and TP53 was pronounced across different tumor grades. Cancer drivers specific to each subtype include TP53, PIK3CA, CDC27, CDH1, STK39, CBFB, MAP3K1, and GATA3, and mutations associated with patient survival were identified in our cohort. CONCLUSIONS: This extensive study has revealed tumor burden, driver genes, co-occurrence, mutual exclusivity, and survival effects of mutations on a US Midwestern breast cancer cohort, paving the way for developing personalized therapeutic strategies.

Transcriptome profile changes in the jejunum of nonhuman primates exposed to supralethal dose of total- or partial-body radiation.

The risk of exposure of the general public or military personnel to high levels of ionizing radiation from nuclear weapons or radiological accidents is a dire national security matter. The development of advanced molecular biodosimetry methods, those that measure biological response, such as transcriptomics, to screen large populations of radiation-exposed victims is key to improving survival outcomes during radiological mass casualty scenarios. In this study, nonhuman primates were exposed to either 12.0 Gy cobalt-60 gamma (total-body irradiation, TBI) or X-ray (partial-body irradiation, PBI) 24 h after administration of a potential radiation medical countermeasure, gamma-tocotrienol (GT3). Changes in the jejunal transcriptomic profiles in GT3-treated and irradiated animals were compared to healthy controls to assess the extent of radiation damage. No major effect of GT3 on radiation-induced transcriptome at this radiation dose was identified. About 80% of the pathways with a known activation or repression state were commonly observed between both exposures. Several common pathways activated due to irradiation include FAK signaling, CREB signaling in the neurons, phagosome formation, and G-protein coupled signaling pathway. Sex-specific differences associated with excessive mortality among irradiated females were identified in this study, including Estrogen receptor signaling. Differential pathway activation was also identified across PBI and TBI, pointing towards altered molecular response for different degrees of bone marrow sparing and radiation doses. This study provides insight into radiation-induced changes in jejunal transcriptional profiles, supporting the investigation for the identification of biomarkers for radiation injury and countermeasure efficacy.

Cell-free DNA in maternal blood and artificial intelligence: accurate prenatal detection of fetal congenital heart defects.

BACKGROUND: DNA cytosine nucleotide methylation (epigenomics and epigenetics) is an important mechanism for controlling gene expression in cardiac development. Combined artificial intelligence and whole-genome epigenomic analysis of circulating cell-free DNA in maternal blood has the potential for the detection of fetal congenital heart defects. OBJECTIVE: This study aimed to use genome-wide DNA cytosine methylation and artificial intelligence analyses of circulating cell-free DNA for the minimally invasive detection of fetal congenital heart defects. STUDY DESIGN: In this prospective study, whole-genome cytosine nucleotide methylation analysis was performed on circulating cell-free DNA using the Illumina Infinium MethylationEPIC BeadChip array. Multiple artificial intelligence approaches were evaluated for the detection of congenital hearts. The Ingenuity Pathway Analysis program was used to identify gene pathways that were epigenetically altered and important in congenital heart defect pathogenesis to further elucidate the pathogenesis of isolated congenital heart defects. RESULTS: There were 12 cases of isolated nonsyndromic congenital heart defects and 26 matched controls. A total of 5918 cytosine nucleotides involving 4976 genes had significantly altered methylation, that is, a P value of <.05 along with ≥5% whole-genome cytosine nucleotide methylation difference, in congenital heart defect cases vs controls. Artificial intelligence analysis of the methylation data achieved excellent congenital heart defect predictive accuracy (areas under the receiver operating characteristic curve, ≥0.92). For example, an artificial intelligence model using a combination of 5 whole-genome cytosine nucleotide markers achieved an area under the receiver operating characteristic curve of 0.97 (95% confidence interval, 0.87-1.0) with 98% sensitivity and 94% specificity. We found epigenetic changes in genes and gene pathways involved in the following important cardiac developmental processes: "cardiovascular system development and function," "cardiac hypertrophy," "congenital heart anomaly," and "cardiovascular disease." This lends biologic plausibility to our findings. CONCLUSION: This study reported the feasibility of minimally invasive detection of fetal congenital heart defect using artificial intelligence and DNA methylation analysis of circulating cell-free DNA for the prediction of fetal congenital heart defect. Furthermore, the findings supported an important role of epigenetic changes in congenital heart defect development.

Critical contributions of protein cargos to the functions of macrophage-derived extracellular vesicles.

BACKGROUND: Macrophages are highly plastic innate immune cells that play key roles in host defense, tissue repair, and homeostasis maintenance. In response to divergent stimuli, macrophages rapidly alter their functions and manifest a wide polarization spectrum with two extremes: M1 or classical activation and M2 or alternative activation. Extracellular vesicles (EVs) secreted from differentially activated macrophages have been shown to have diverse functions, which are primarily attributed to their microRNA cargos. The role of protein cargos in these EVs remains largely unexplored. Therefore, in this study, we focused on the protein cargos in macrophage-derived EVs. RESULTS: Naïve murine bone marrow-derived macrophages were treated with lipopolysaccharide or interlukin-4 to induce M1 or M2 macrophages, respectively. The proteins of EVs and their parental macrophages were subjected to quantitative proteomics analyses, followed by bioinformatic analyses. The enriched proteins of M1-EVs were involved in proinflammatory pathways and those of M2-EVs were associated with immunomodulation and tissue remodeling. The signature proteins of EVs shared a limited subset of the proteins of their respective progenitor macrophages, but they covered many of the typical pathways and functions of their parental cells, suggesting their respective M1-like and M2-like phenotypes and functions. Experimental examination validated that protein cargos in M1- or M2-EVs induced M1 or M2 polarization, respectively. More importantly, proteins in M1-EVs promoted viability, proliferation, and activation of T lymphocytes, whereas proteins in M2-EVs potently protected the tight junction structure and barrier integrity of epithelial cells from disruption. Intravenous administration of M2-EVs in colitis mice led to their accumulation in the colon, alleviation of colonic inflammation, promotion of M2 macrophage polarization, and improvement of gut barrier functions. Protein cargos in M2-EVs played a key role in their protective function in colitis. CONCLUSION: This study has yielded a comprehensive unbiased dataset of protein cargos in macrophage-derived EVs, provided a systemic view of their potential functions, and highlighted the important engagement of protein cargos in the pathophysiological functions of these EVs.

Interplay of CodY and CcpA in Regulating Central Metabolism and Biofilm Formation in Staphylococcus aureus.

Staphylococcus aureus is a medically important pathogen with high metabolic versatility allowing it to infect various niches within a host. S. aureus utilizes two major transcriptional regulators, namely, CodY and CcpA, to remodel metabolic and virulence gene expression in response to changing environmental conditions. Previous studies revealed that inactivation of either codY or ccpA has a pronounced impact on different aspects of staphylococcal physiology and pathogenesis. To determine the contribution and interplay of these two regulators in modulating central metabolism, virulence, and biofilm development, we constructed and characterized the codY ccpA double mutant in S. aureus UAMS-1. In line with previous studies, we found that CcpA and CodY control the cellular metabolic status by altering carbon flux through the central and overflow metabolic pathways. Our results demonstrate that ccpA inactivation impairs biofilm formation and decreases incorporation of extracellular DNA (eDNA) into the biofilm matrix, whereas disrupting codY resulted in a robust structured biofilm tethered together with eDNA and polysaccharide intercellular adhesin (PIA). Interestingly, inactivation of both codY and ccpA decreases biofilm biomass and reduces eDNA release in the double mutant. Compared with the inactivation of codY, the codY ccpA mutant did not overexpress toxins but maintained overexpression of amino acid metabolism pathways. Furthermore, the codY ccpA mutant produced large amounts of PIA, in contrast to the wild-type strain and ccpA mutant. Combined, the results of this study suggest that the coordinated action of CodY and CcpA modulate central metabolism, virulence gene expression, and biofilm-associated genes to optimize growth on preferred carbon sources until starvation sets in. IMPORTANCE Staphylococcus aureus is a leading cause of biofilm-associated infections, including infective endocarditis, worldwide. A greater understanding of metabolic forces driving biofilm formation in S. aureus is essential for the identification of novel therapeutic targets and for the development of new strategies to combat this medically important pathogen. This study characterizes the interplay and regulation of central metabolism and biofilm development by two global transcriptional regulators, CodY and CcpA. We found that the lack of CcpA and/or CodY have different impacts on intracellular metabolic status leading to a formation of morphologically altered biofilms. Overall, the results of this study provide new insights into our understanding of metabolism-mediated regulation of biofilm development in S. aureus.

Maternal opioid use disorder: Placental transcriptome analysis for neonatal opioid withdrawal syndrome.

Excessive prenatal opioid exposure may lead to the development of Neonatal Opioid Withdrawal Syndrome (NOWS). RNA-seq was done on 64 formalin-fixed paraffin-embedded placental tissue samples from 32 mothers with opioid use disorder, with newborns with NOWS that required treatment, and 32 prenatally unexposed controls. We identified 93 differentially expressed genes in the placentas of infants with NOWS compared to unexposed controls. There were 4 up- and 89 downregulated genes. Among these, 7 genes CYP1A1, APOB, RPH3A, NRXN1, LINC01206, AL157396.1, UNC80 achieved an FDR p-value of <0.01. The remaining 87 genes were significant with FDR p-value <0.05. The 4 upregulated, CYP1A1, FP671120.3, RAD1, RN7SL856P, and the 10 most significantly downregulated genes were RNA5SP364, GRIN2A, UNC5D, DMBT1P1, MIR3976HG, LINC02199, LINC02822, PANTR1, AC012178.1, CTNNA2. Ingenuity Pathway Analysis identified the 7 most likely to play an important role in the etiology of NOWS. Our study expands insights into the genetic mechanisms of NOWS development.

Placental DNA methylation profiles in opioid-exposed pregnancies and associations with the neonatal opioid withdrawal syndrome.

Opioid abuse during pregnancy can result in Neonatal Opioid Withdrawal Syndrome (NOWS). We investigated genome-wide methylation analyses of 96 placental tissue samples, including 32 prenatally opioid-exposed infants with NOWS who needed therapy (+Opioids/+NOWS), 32 prenatally opioid-exposed infants with NOWS who did not require treatment (+Opioids/-NOWS), and 32 prenatally unexposed controls (-Opioids/-NOWS, control). Statistics, bioinformatics, Artificial Intelligence (AI), including Deep Learning (DL), and Ingenuity Pathway Analyses (IPA) were performed. We identified 17 dysregulated pathways thought to be important in the pathophysiology of NOWS and reported accurate AI prediction of NOWS diagnoses. The DL had an AUC (95% CI) =0.98 (0.95-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS from the +Opioids/-NOWS group and AUCs (95% CI) =1.00 (1.0-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS versus control and + Opioids/-NOWS group versus controls. This study provides strong evidence of methylation dysregulation of placental tissue in NOWS development.

Decoding the Synaptic Proteome with Long-Term Exposure to Midazolam during Early Development.

The intensive use of anesthetic and sedative agents in the neonatal intensive care unit (NICU) has raised controversial concerns about the potential neurodevelopmental risks. This study focused on midazolam (MDZ), a common benzodiazepine regularly used as a sedative on neonates in the NICU. Mounting evidence suggests a single exposure to MDZ during the neonatal period leads to learning disturbances. However, a knowledge gap that remains is how long-term exposure to MDZ during very early stages of life impacts synaptic alterations. Using a preclinical rodent model system, we mimicked a dose-escalation regimen on postnatal day 3 (P3) pups until day 21. Next, purified synaptosomes from P21 control and MDZ animals were subjected to quantitative mass-spectrometry-based proteomics, to identify potential proteomic signatures. Further analysis by ClueGO identified enrichment of proteins associated with actin-binding and protein depolymerization process. One potential hit identified was alpha adducin (ADD1), belonging to the family of cytoskeleton proteins, which was upregulated in the MDZ group and whose expression was further validated by Western blot. In summary, this study sheds new information on the long-term exposure of MDZ during the early stages of development impacts synaptic function, which could subsequently perturb neurobehavioral outcomes at later stages of life.

Hypo-glycosylated hFSH drives ovarian follicular development more efficiently than fully-glycosylated hFSH: enhanced transcription and PI3K and MAPK signaling.

STUDY QUESTION: Does hypo-glycosylated human recombinant FSH (hFSH18/21) have greater in vivo bioactivity that drives follicle development in vivo compared to fully-glycosylated human recombinant FSH (hFSH24)? SUMMARY ANSWER: Compared with fully-glycosylated hFSH, hypo-glycosylated hFSH has greater bioactivity, enabling greater follicular health and growth in vivo, with enhanced transcriptional activity, greater activation of receptor tyrosine kinases (RTKs) and elevated phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and Mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling. WHAT IS KNOWN ALREADY: Glycosylation of FSH is necessary for FSH to effectively activate the FSH receptor (FSHR) and promote preantral follicular growth and formation of antral follicles. In vitro studies demonstrate that compared to fully-glycosylated recombinant human FSH, hypo-glycosylated FSH has greater activity in receptor binding studies, and more effectively stimulates the PKA pathway and steroidogenesis in human granulosa cells. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study evaluating the actions of purified recombinant human FSH glycoforms on parameters of follicular development, gene expression and cell signaling in immature postnatal day (PND) 17 female CD-1 mice. To stimulate follicle development in vivo, PND 17 female CD-1 mice (n = 8-10/group) were treated with PBS (150 µl), hFSH18/21 (1 µg/150 µl PBS) or hFSH24 (1 µg/150 µl PBS) by intraperitoneal injection (i.p.) twice daily (8:00 a.m. and 6:00 p.m.) for 2 days. Follicle numbers, serum anti-Müllerian hormone (AMH) and estradiol levels, and follicle health were quantified. PND 17 female CD-1 mice were also treated acutely (2 h) in vivo with PBS, hFSH18/21 (1 µg) or hFSH24 (1 µg) (n = 3-4/group). One ovary from each mouse was processed for RNA sequencing analysis and the other ovary processed for signal transduction analysis. An in vitro ovary culture system was used to confirm the relative signaling pathways. PARTICIPANTS/MATERIALS, SETTING, METHODS: The purity of different recombinant hFSH glycoforms was analyzed using an automated western blot system. Follicle numbers were determined by counting serial sections of the mouse ovary. Real-time quantitative RT-PCR, western blot and immunofluorescence staining were used to determine growth and apoptosis markers related with follicle health. RNA sequencing and bioinformatics were used to identify pathways and processes associated with gene expression profiles induced by acute FSH glycoform treatment. Analysis of RTKs was used to determine potential FSH downstream signaling pathways in vivo. Western blot and in vitro ovarian culture system were used to validate the relative signaling pathways. MAIN RESULTS AND THE ROLE OF CHANCE: Our present study shows that both hypo- and fully-glycosylated recombinant human FSH can drive follicular growth in vivo. However, hFSH18/21 promoted development of significantly more large antral follicles compared to hFSH24 (P < 0.01). In addition, compared with hFSH24, hFSH18/21 also promoted greater indices of follicular health, as defined by lower BAX/BCL2 ratios and reduced cleaved Caspase 3. Following acute in vivo treatment with FSH glycoforms RNA-sequencing data revealed that both FSH glycoforms rapidly induced ovarian transcription in vivo, but hypo-glycosylated FSH more robustly stimulated Gαs and cAMP-mediated signaling and members of the AP-1 transcription factor complex. Moreover, hFSH18/21 treatment induced significantly greater activation of RTKs, PI3K/AKT and MAPK/ERK signaling compared to hFSH24. FSH-induced indices of follicle growth in vitro were blocked by inhibition of PI3K and MAPK. LARGE SCALE DATA: RNA sequencing of mouse ovaries. Data will be shared upon reasonable request to the corresponding author. LIMITATIONS, REASONS FOR CAUTION: The observations that hFSH glycoforms have different bioactivities in the present study employing a mouse model of follicle development should be verified in nonhuman primates. The gene expression studies reflect transcriptomes of whole ovaries. WIDER IMPLICATIONS OF THE FINDINGS: Commercially prepared recombinant human FSH used for ovarian stimulation in human ART is fully-glycosylated FSH. Our findings that hypo-glycosylated hFSH has greater bioactivity enabling greater follicular health and growth without exaggerated estradiol production in vivo, demonstrate the potential for its development for application in human ART. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by NIH 1P01 AG029531, NIH 1R01 HD 092263, VA I01 BX004272, and the Olson Center for Women's Health. JSD is the recipient of a VA Senior Research Career Scientist Award (1IK6 BX005797). This work was also partially supported by National Natural Science Foundation of China (No. 31872352). The authors declared there are no conflicts of interest.

Functional, proteomic and bioinformatic analyses of Nrf2- and Keap1- null skeletal muscle.

KEY POINTS: Nrf2 is a master regulator of endogenous cellular defences, governing the expression of more than 200 cytoprotective proteins, including a panel of antioxidant enzymes. Nrf2 plays an important role in redox haemostasis of skeletal muscle in response to the increased generation of reactive oxygen species during contraction. Employing skeletal muscle-specific transgenic mouse models with unbiased-omic approaches, we uncovered new target proteins, downstream pathways and molecular networks of Nrf2 in skeletal muscle following Nrf2 or Keap1 deletion. Based on the findings, we proposed a two-way model to understand Nrf2 function: a tonic effect through a Keap1-independent mechanism under basal conditions and an induced effect through a Keap1-dependent mechanism in response to oxidative and other stresses. ABSTRACT: Although Nrf2 has been recognized as a master regulator of cytoprotection, its functional significance remains to be completely defined. We hypothesized that proteomic/bioinformatic analyses from Nrf2-deficient or overexpressed skeletal muscle tissues will provide a broader spectrum of Nrf2 targets and downstream pathways than are currently known. To this end, we created two transgenic mouse models; the iMS-Nrf2flox/flox and iMS-Keap1flox/flox , employing which we demonstrated that selective deletion of skeletal muscle Nrf2 or Keap1 separately impaired or improved skeletal muscle function. Mass spectrometry revealed that Nrf2-KO changed expression of 114 proteins while Keap1-KO changed expression of 117 proteins with 10 proteins in common between the groups. Gene ontology analysis suggested that Nrf2 KO-changed proteins are involved in metabolism of oxidoreduction coenzymes, purine ribonucleoside triphosphate, ATP and propanoate, which are considered as the basal function of Nrf2, while Keap1 KO-changed proteins are involved in cellular detoxification, NADP metabolism, glutathione metabolism and the electron transport chain, which belong to the induced effect of Nrf2. Canonical pathway analysis suggested that Keap1-KO activated four pathways, whereas Nrf2-KO did not. Ingenuity pathway analysis further revealed that Nrf2-KO and Keap1-KO impacted different signal proteins and functions. Finally, we validated the proteomic and bioinformatics data by analysing glutathione metabolism and mitochondrial function. In conclusion, we found that Nrf2-targeted proteins are assigned to two groups: one mediates the tonic effects evoked by a low level of Nrf2 at basal condition; the other is responsible for the inducible effects evoked by a surge of Nrf2 that is dependent on a Keap1 mechanism.

Red panda: a novel method for detecting variants in single-cell RNA sequencing.

BACKGROUND: Single-cell sequencing enables us to better understand genetic diseases, such as cancer or autoimmune disorders, which are often affected by changes in rare cells. Currently, no existing software is aimed at identifying single nucleotide variations or micro (1-50 bp) insertions and deletions in single-cell RNA sequencing (scRNA-seq) data. Generating high-quality variant data is vital to the study of the aforementioned diseases, among others. RESULTS: In this study, we report the design and implementation of Red Panda, a novel method to accurately identify variants in scRNA-seq data. Variants were called on scRNA-seq data from human articular chondrocytes, mouse embryonic fibroblasts (MEFs), and simulated data stemming from the MEF alignments. Red Panda had the highest Positive Predictive Value at 45.0%, while other tools-FreeBayes, GATK HaplotypeCaller, GATK UnifiedGenotyper, Monovar, and Platypus-ranged from 5.8-41.53%. From the simulated data, Red Panda had the highest sensitivity at 72.44%. CONCLUSIONS: We show that our method provides a novel and improved mechanism to identify variants in scRNA-seq as compared to currently existing software. However, methods for identification of genomic variants using scRNA-seq data can be still improved.

Proximal tubule cyclophilin D regulates fatty acid oxidation in cisplatin-induced acute kidney injury.

Regardless of the etiology, acute kidney injury involves aspects of mitochondrial dysfunction and ATP depletion. Fatty acid oxidation is the preferred energy source of the kidney and is inhibited during acute kidney injury. A pivotal role for the mitochondrial matrix protein, cyclophilin D in regulating overall cell metabolism is being unraveled. We hypothesize that mitochondrial interaction of proximal tubule cyclophilin D and the transcription factor PPARα modulate fatty acid beta-oxidation in cisplatin-induced acute kidney injury. Cisplatin injury resulted in histological and functional damage in the kidney with downregulation of fatty acid oxidation genes and increase of intrarenal lipid accumulation. However, proximal tubule-specific deletion of cyclophilin D protected the kidneys from the aforementioned effects. Mitochondrial translocation of PPARα, its binding to cyclophilin D, and sequestration led to inhibition of its nuclear translocation and transcription of PPARα-regulated fatty acid oxidation genes during cisplatin-induced acute kidney injury. Genetic or pharmacological inhibition of cyclophilin D preserved nuclear expression and transcriptional activity of PPARα and prevented the impairment of fatty acid oxidation and intracellular lipid accumulation. Docking analysis identified potential binding sites between PPARα and cyclophilin D. Thus, our results indicate that proximal tubule cyclophilin D elicits impaired mitochondrial fatty acid oxidation via mitochondrial interaction between cyclophilin D and PPARα. Hence, targeting their interaction may be a potential therapeutic strategy to prevent energy depletion, lipotoxicity and cell death in cisplatin-induced acute kidney injury.

ChimeRScope: a novel alignment-free algorithm for fusion transcript prediction using paired-end RNA-Seq data.

The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The 'fusion' or 'chimeric' transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as k-mers) profiles of the RNA-Seq paired-end reads. Results on published datasets and in-house cancer cell line datasets followed by experimental validations demonstrate that ChimeRScope consistently outperforms other popular methods irrespective of the read lengths and sequencing depth. More importantly, results on our in-house datasets show that ChimeRScope is a better tool that is capable of identifying novel fusion transcripts with potential oncogenic functions. ChimeRScope is accessible as a standalone software at (https://github.com/ChimeRScope/ChimeRScope/wiki) or via the Galaxy web-interface at (https://galaxy.unmc.edu/).

Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic predictors of CP in newborns and to investigate disease pathogenesis. Methylation analysis of newborn blood DNA using an Illumina HumanMethylation450K array was performed in 23 CP cases and 21 unaffected controls. There were 230 significantly differentially-methylated CpG loci in 258 genes. Each locus had at least 2.0-fold change in methylation in CP versus controls with a FDR p-value ≤ 0.05. Methylation level for each CpG locus had an area under the receiver operating curve (AUC) ≥ 0.75 for CP detection. Using Artificial Intelligence (AI) platforms/Machine Learning (ML) analysis, CpG methylation levels in a combination of 230 significantly differentially-methylated CpG loci in 258 genes had a 95% sensitivity and 94.4% specificity for newborn prediction of CP. Using pathway analysis, multiple canonical pathways plausibly linked to neuronal function were over-represented. Altered biological processes and functions included: neuromotor damage, malformation of major brain structures, brain growth, neuroprotection, neuronal development and de-differentiation, and cranial sensory neuron development. In conclusion, blood leucocyte epigenetic changes analyzed using AI/ML techniques appeared to accurately predict CP and provided plausible mechanistic information on CP pathogenesis.

Motifome comparison between modern human, Neanderthal and Denisovan.

BACKGROUND: The availability of the genomes of two archaic humans, Neanderthal and Denisovan, and that of modern humans provides researchers an opportunity to investigate genetic differences between these three subspecies on a genome-wide scale. Here we describe an algorithm that predicts statistically significant motifs based on the difference between a given motif's actual and expected distributions. The algorithm was previously applied to plants but was modified for this work. RESULTS: The result of applying the algorithm to the human, Neanderthal, and Denisovan genomes is a catalog of potential regulatory motifs in these three human subspecies. We examined the distributions of these motifs in genetic elements including human retroviruses, human accelerated regions, and human accelerated conserved noncoding sequences regions. Differences in these distributions could be the origin of differences in phenotype between the three subspecies. Twenty significant motifs common to all three genomes were found; thirty-three were found in endogenous retroviruses in Neanderthal and Denisovan. Ten of these motifs mapped to the 22 bp core of MiR-1304. The core of this genetic element regulates the ENAM and AMTN genes, which take part in odontogenesis and whose 3' UTRs contained significant motifs. The introns of 20 genes were found to contain a large number of significant motifs, which were also overrepresented in 49 human accelerated regions. These genes include NAV2, SorCS2, TRAPPC9, GRID1, PRDM16, CAMTA1, and ASIC which are all involved in neuroregulation. Further analysis of these genes using the GO database indicates that many are associated with neurodevelopment. Also, varying numbers of significant motifs were found to occur in regions of the Neanderthal and Denisovan genomes that are missing from the human genome, suggesting further functional differences between modern and archaic humans. CONCLUSION: Although Neanderthal and Denisovan are now extinct, detailed examination of elements from their genomes can shed light on possible phenotypic and cognitive differences between these two archaic human subspecies and modern humans. Genetic similarities and differences between these three subspecies and other fossil hominids would also be of interest.

Whole genomic sequence analysis of Bacillus infantis: defining the genetic blueprint of strain NRRL B-14911, an emerging cardiopathogenic microbe.

BACKGROUND: We recently reported the identification of Bacillus sp. NRRL B-14911 that induces heart autoimmunity by generating cardiac-reactive T cells through molecular mimicry. This marine bacterium was originally isolated from the Gulf of Mexico, but no associations with human diseases were reported. Therefore, to characterize its biological and medical significance, we sought to determine and analyze the complete genome sequence of Bacillus sp. NRRL B-14911. RESULTS: Based on the phylogenetic analysis of 16S ribosomal RNA (rRNA) genes, sequence analysis of the 16S-23S rDNA intergenic transcribed spacers, phenotypic microarray, and matrix-assisted laser desorption ionization time-of-flight mass spectrometry, we propose that this organism belongs to the species Bacillus infantis, previously shown to be associated with sepsis in a newborn child. Analysis of the complete genome of Bacillus sp. NRRL B-14911 revealed several virulence factors including adhesins, invasins, colonization factors, siderophores and transporters. Likewise, the bacterial genome encodes a wide range of methyl transferases, transporters, enzymatic and biochemical pathways, and insertion sequence elements that are distinct from other closely related bacilli. CONCLUSIONS: The complete genome sequence of Bacillus sp. NRRL B-14911 provided in this study may facilitate genetic manipulations to assess gene functions associated with bacterial survival and virulence. Additionally, this bacterium may serve as a useful tool to establish a disease model that permits systematic analysis of autoimmune events in various susceptible rodent strains.

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.

BACKGROUND: Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. RESULTS: ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and vitamins. CONCLUSIONS: The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems.

Identification of the human PMR1 mRNA endonuclease as an alternatively processed product of the gene for peroxidasin-like protein.

The PMR1 endonuclease was discovered in Xenopus liver and identified as a member of the large and diverse peroxidase gene family. The peroxidase genes arose from multiple duplication and rearrangement events, and their high degree of sequence similarity confounded attempts to identify human PMR1. The functioning of PMR1 in mRNA decay depends on the phosphorylation of a tyrosine in the C-terminal polysome targeting domain by c-Src. The sequences of regions that are required for c-Src binding and phosphorylation of Xenopus PMR1 were used to inform a bioinformatics search that identified two related genes as potential candidates for human PMR1: peroxidasin homolog (PXDN) and peroxidasin homolog-like (PXDNL) protein. Although each of these genes is predicted to encode a large, multidomain membrane-bound peroxidase, alternative splicing of PXDNL pre-mRNA yields a transcript whose predicted product is a 57-kDa protein with 42% sequence identity to Xenopus PMR1. Results presented here confirm the existence of the predicted 57-kDa protein, show this is the only form of PXDNL detected in any of the human cell lines examined, and confirm its identity as human PMR1. Like the Xenopus protein, human PMR1 binds to c-Src, is tyrosine phosphorylated, sediments on polysomes, and catalyzes the selective decay of a PMR1 substrate mRNA. Importantly, the expression of human PMR1 stimulates cell motility in a manner similar to that of the Xenopus PMR1 expressed in human cells, thus providing definitive evidence linking endonuclease decay to the regulation of cell motility.