Transitions of blood immune endotypes and improved outcome by anakinra in COVID-19 pneumonia: an analysis of the SAVE-MORE randomized controlled trial.

BACKGROUND: Endotype classification may guide immunomodulatory management of patients with bacterial and viral sepsis. We aimed to identify immune endotypes and transitions associated with response to anakinra (human interleukin 1 receptor antagonist) in participants in the SAVE-MORE trial. METHODS: Adult patients hospitalized with radiological findings of PCR-confirmed severe pneumonia caused by SARS-CoV-2 and plasma-soluble urokinase plasminogen activator receptor levels of ≥ 6 ng/ml in the SAVE-MORE trial (NCT04680949) were characterized at baseline and days 4 and 7 of treatment using a previously defined 33-messenger RNA classifier to assign an immunological endotype in blood. Endpoints were changes in endotypes and progression to severe respiratory failure (SRF) associated with anakinra treatment. RESULTS: At baseline, 23.2% of 393 patients were designated as inflammopathic, 41.1% as adaptive, and 35.7% as coagulopathic. Only 23.9% were designated as the same endotype at days 4 and 7 compared to baseline, while all other patients transitioned between endotypes. Anakinra-treated patients were more likely to remain in the adaptive endotype during 7-day treatment (24.4% vs. 9.9%; p < 0.001). Anakinra also protected patients with coagulopathic endotype at day 7 against SRF compared to placebo (27.8% vs. 55.9%; p = 0.013). CONCLUSION: We identify an association between endotypes defined using blood transcriptome and anakinra therapy for COVID-19 pneumonia, with anakinra-treated patients shifting toward endotypes associated with a better outcome, mainly the adaptive endotype. Trial registration ClinicalTrials.gov, NCT04680949, December 23, 2020.

Multisite validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza.

BACKGROUND: Indiscriminate use of antimicrobials and antimicrobial resistance is a public health threat. IMX-BVN-1, a 29-host mRNA classifier, provides two separate scores that predict likelihoods of bacterial and viral infections in patients with suspected acute infections. We validated the performance of IMX-BVN-1 in adults attending acute health care settings with suspected influenza. METHOD: We amplified 29-host response genes in RNA extracted from blood by NanoString nCounter. IMX-BVN-1 calculated two scores to predict probabilities of bacterial and viral infections. Results were compared against the infection status (no infection; highly probable/possible infection; confirmed infection) determined by clinical adjudication. RESULTS: Amongst 602 adult patients (74.9% ED, 16.9% ICU, 8.1% outpatients), 7.6% showed in-hospital mortality and 15.5% immunosuppression. Median IMX-BVN-1 bacterial and viral scores were higher in patients with confirmed bacterial (0.27) and viral (0.62) infections than in those without bacterial (0.08) or viral (0.21) infection, respectively. The AUROC distinguishing bacterial from nonbacterial illness was 0.81 and 0.87 when distinguishing viral from nonviral illness. The bacterial top quartile's positive likelihood ratio (LR) was 4.38 with a rule-in specificity of 88%; the bacterial bottom quartile's negative LR was 0.13 with a rule-out sensitivity of 96%. Similarly, the viral top quartile showed an infinite LR with rule-in specificity of 100%; the viral bottom quartile had a LR of 0.22 and a rule-out sensitivity of 85%. CONCLUSION: IMX-BVN-1 showed high accuracy for differentiating bacterial and viral infections from noninfectious illness in patients with suspected influenza. Clinical utility of IMX-BVN will be validated following integration into a point of care system.

Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients.

Importance: Rapid and accurate discrimination of sepsis and its potential severity currently require multiple assays with slow processing times that are often inconclusive in discerning sepsis from sterile inflammation. Objective: To analyze a whole-blood, multivalent, host-messenger RNA expression metric for estimating the likelihood of bacterial infection and 30-day mortality and compare performance of the metric with that of other diagnostic and prognostic biomarkers and clinical parameters. Design, Setting, and Participants: This prospective diagnostic and prognostic study was performed in the surgical intensive care unit (ICU) of a single, academic health science center. The analysis included 200 critically ill adult patients admitted with suspected sepsis (cohort A) or those at high risk for developing sepsis (cohort B) between July 1, 2020, and July 30, 2021. Exposures: Whole-blood sample measurements of a custom 29-messenger RNA transcriptomic metric classifier for likelihood of bacterial infection (IMX-BVN-3) or 30-day mortality (severity) (IMX-SEV-3) in a clinical-diagnostic laboratory setting using an analysis platform (510[k]-cleared nCounter FLEX; NanoString, Inc), compared with measurement of procalcitonin and interleukin 6 (IL-6) plasma levels, and maximum 24-hour sequential organ failure assessment (SOFA) scores. Main Outcomes and Measures: Estimated sepsis and 30-day mortality performance. Results: Among the 200 patients included (124 men [62.0%] and 76 women [38.0%]; median age, 62.5 [IQR, 47.0-72.0] years), the IMX-BVN-3 bacterial infection classifier had an area under the receiver operating characteristics curve (AUROC) of 0.84 (95% CI, 0.77-0.90) for discriminating bacterial infection at ICU admission, similar to procalcitonin (0.85 [95% CI, 0.79-0.90]; P = .79) and significantly better than IL-6 (0.67 [95% CI, 0.58-0.75]; P < .001). For estimating 30-day mortality, the IMX-SEV-3 metric had an AUROC of 0.81 (95% CI, 0.66-0.95), which was significantly better than IL-6 levels (0.57 [95% CI, 0.37-0.77]; P = .006), marginally better than procalcitonin levels (0.65 [95% CI, 0.50-0.79]; P = .06), and similar to the SOFA score (0.76 [95% CI, 0.62-0.91]; P = .48). Combining IMX-BVN-3 and IMX-SEV-3 with procalcitonin or IL-6 levels or SOFA scores did not significantly improve performance. Among patients with sepsis, IMX-BVN-3 scores decreased over time, reflecting the resolution of sepsis. In 11 individuals at high risk (cohort B) who subsequently developed sepsis during their hospital course, IMX-BVN-3 bacterial infection scores did not decline over time and peaked on the day of documented infection. Conclusions and Relevance: In this diagnostic and prognostic study, a novel, multivalent, transcriptomic metric accurately estimated the presence of bacterial infection and risk for 30-day mortality in patients admitted to a surgical ICU. The performance of this single transcriptomic metric was equivalent to or better than multiple alternative diagnostic and prognostic metrics when measured at admission and provided additional information when measured over time.

A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

A Transcriptomic Severity Metric That Predicts Clinical Outcomes in Critically Ill Surgical Sepsis Patients.

OBJECTIVES: Clinically deployable methods for the rapid and accurate prediction of sepsis severity that could elicit a meaningful change in clinical practice are currently lacking. We evaluated a whole-blood, multiplex host-messenger RNA expression metric, Inflammatix-Severity-2, for identifying septic, hospitalized patients' likelihood of 30-day mortality, development of chronic critical illness, discharge disposition, and/or secondary infections. DESIGN: Retrospective, validation cohort analysis. SETTING: Single, academic health center ICU. PATIENTS: Three hundred thirty-five critically ill adult surgical patients with sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Whole blood was collected in PAXgene Blood RNA collection tubes at 24 hours after sepsis diagnosis and analyzed using a custom 29-messenger RNA classifier (Inflammatix-Severity-2) in a Clinical Laboratory Improvement Amendments certified diagnostic laboratory using the NanoString FLEX platform. Among patients meeting Sepsis-3 criteria, the Inflammatix-Severity-2 severity score was significantly better (p < 0.05) at predicting secondary infections (area under the receiver operating curve 0.71) and adverse clinical outcomes (area under the receiver operating curve 0.75) than C-reactive protein, absolute lymphocyte counts, total WBC count, age, and Charlson comorbidity index (and better, albeit nonsignificantly, than interleukin-6 and Acute Physiology and Chronic Health Evaluation II). Using multivariate logistic regression analysis, only combining the Charlson comorbidity index (area under the receiver operating curve 0.80) or Acute Physiology and Chronic Health Evaluation II (area under the receiver operating curve 0.81) with Inflammatix-Severity-2 significantly improved prediction of adverse clinical outcomes, and combining with the Charlson comorbidity index for predicting 30-day mortality (area under the receiver operating curve 0.79). CONCLUSIONS: The Inflammatix-Severity-2 severity score was superior at predicting secondary infections and overall adverse clinical outcomes compared with other common metrics. Combining a rapidly measured transcriptomic metric with clinical or physiologic indices offers the potential to optimize risk-based resource utilization and patient management adjustments that may improve outcomes in surgical sepsis. Hospitalized patients who are septic and present with an elevated IMX-SEV2 severity score and preexisting comorbidities may be ideal candidates for clinical interventions aimed at reducing the risk of secondary infections and adverse clinical outcomes.

Optimization of Genomic Classifiers for Clinical Deployment: Evaluation of Bayesian Optimization to Select Predictive Models of Acute Infection and In-Hospital Mortality.

Acute infection, if not rapidly and accurately detected, can lead to sepsis, organ failure and even death. Current detection of acute infection as well as assessment of a patient's severity of illness are imperfect. Characterization of a patient's immune response by quantifying expression levels of specific genes from blood represents a potentially more timely and precise means of accomplishing both tasks. Machine learning methods provide a platform to leverage this host response for development of deployment-ready classification models. Prioritization of promising classifiers is dependent, in part, on hyperparameter optimization for which a number of approaches including grid search, random sampling and Bayesian optimization have been shown to be effective. We compare HO approaches for the development of diagnostic classifiers of acute infection and in-hospital mortality from gene expression of 29 diagnostic markers. We take a deployment-centered approach to our comprehensive analysis, accounting for heterogeneity in our multi-study patient cohort with our choices of dataset partitioning and hyperparameter optimization objective as well as assessing selected classifiers in external (as well as internal) validation. We find that classifiers selected by Bayesian optimization for in-hospital mortality can outperform those selected by grid search or random sampling. However, in contrast to previous research: 1) Bayesian optimization is not more efficient in selecting classifiers in all instances compared to grid search or random sampling-based methods and 2) we note marginal gains in classifier performance in only specific circumstances when using a common variant of Bayesian optimization (i.e. automatic relevance determination). Our analysis highlights the need for further practical, deployment-centered benchmarking of HO approaches in the healthcare context.

Validation of Inflammopathic, Adaptive, and Coagulopathic Sepsis Endotypes in Coronavirus Disease 2019.

OBJECTIVES: Complex critical syndromes like sepsis and coronavirus disease 2019 may be composed of underling "endotypes," which may respond differently to treatment. The aim of this study was to test whether a previously defined bacterial sepsis endotypes classifier recapitulates the same clinical and immunological endotypes in coronavirus disease 2019. DESIGN: Prospective single-center observational cohort study. SETTING: Patients were enrolled in Athens, Greece, and blood was shipped to Inflammatix (Burlingame, CA) for analysis. PATIENTS: Adult patients within 24 hours of hospital admission with coronavirus disease 2019 confirmed by polymerase chain reaction and chest radiography. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We studied 97 patients with coronavirus disease 2019, of which 50 went on to severe respiratory failure (SRF) and 16 died. We applied a previously defined 33-messenger RNA classifier to assign endotype (Inflammopathic, Adaptive, or Coagulopathic) to each patient. We tested endotype status against other clinical parameters including laboratory values, severity scores, and outcomes. Patients were assigned as Inflammopathic (29%), Adaptive (44%), or Coagulopathic (27%), similar to our prior study in bacterial sepsis. Adaptive patients had lower rates of SRF and no deaths. Coagulopathic and Inflammopathic endotypes had 42% and 18% mortality rates, respectively. The Coagulopathic group showed highest d-dimers, and the Inflammopathic group showed highest C-reactive protein and interleukin-6 levels. CONCLUSIONS: Our predefined 33-messenger RNA endotypes classifier recapitulated immune phenotypes in viral sepsis (coronavirus disease 2019) despite its prior training and validation only in bacterial sepsis. Further work should focus on continued validation of the endotypes and their interaction with immunomodulatory therapy.

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.

Genotypic divergence in mouse oocyte transcriptomes: possible pathways to hybrid vigor impacting fertility and embryogenesis.

What causes hybrid vigor phenotypes in mammalian oocytes and preimplantation embryos? Answering this question should provide new insight into determinants of oocyte and embryo quality and infertility. Hybrid vigor could arise through a variety of mechanisms, many of which must operate through posttranscriptional mechanisms affecting oocyte mRNA accumulation, stability, translation, and degradation. The differential regulation of such mRNAs may impact essential pathways and functions within the oocyte. We conducted in-depth transcriptome comparisons of immature and mature oocytes of C57BL/6J and DBA/2J inbred strains and C57BL/6J × DBA/2J F1 (BDF1) hybrid oocytes with RNA sequencing, combined with novel computational methods of analysis. We observed extensive differences in mRNA expression and regulation between parental inbred strains and between inbred and hybrid genotypes, including mRNAs encoding proposed markers of oocyte quality. Unique BDF1 oocyte characteristics arise through a combination of additive dominance and incomplete dominance features in the transcriptome, with a lesser degree of transgressive mRNA expression. Special features of the BDF1 transcriptome most prominently relate to histone expression, mitochondrial function, and oxidative phosphorylation. The study reveals the major underlying mechanisms that contribute to superior properties of hybrid oocytes in a mouse model.

Temporal patterns of gene regulation and upstream regulators contributing to major developmental transitions during Rhesus macaque preimplantation development.

The preimplantation period of life in mammals encompasses a tremendous amount of restructuring and remodeling of the embryonic genome and reprogramming of gene expression. These vast changes support metabolic activation and cellular processes that drive early cleavage divisions and enable the creation of the earliest primitive cell lineages. A major question in mammalian embryology is how such vast, sweeping changes in gene expression are orchestrated, so that changes in gene expression are exactly appropriate to meet the developmental needs of the embryo over time. Using the rhesus macaque as an experimentally tractable model species closely related to the human, we combined high quality RNA-seq libraries, in-depth sequencing and advanced systems analysis to discover the underlying mechanisms that drive major changes in gene regulation during preimplantation development. We identified the major changes in mRNA population and the biological pathways and processes impacted by those changes. Most importantly, we identified 24 key upstream regulators that are themselves modulated during development and that are associated with the regulation of over 1000 downstream genes. Through their roles in extensive gene networks, these 24 upstream regulators are situated to either drive major changes in target gene expression or modify the cellular environment in which other genes function, thereby directing major developmental transitions in the preimplantation embryo. The data presented here highlight some of the specific molecular features that likely drive preimplantation development in a nonhuman primate species and provides an extensive database for novel hypothesis-driven studies.

Pilot study of a novel serum mRNA gene panel for diagnosis of acute septic arthritis.

BACKGROUND: Septic arthritis is an orthopedic emergency requiring immediate surgical intervention. Current diagnostic standard of care is an invasive joint aspiration. Aspirations provide information about the inflammatory cells in the sample within a few hours, but there is often ambiguity about whether the source is infectious (e.g. bacterial) or non-infectious (e.g. gout). Cultures can take days to result, so decisions about surgery are often made with incomplete data. Novel diagnostics are thus needed. The "Sepsis MetaScore" (SMS) is an 11-mRNA host immune blood signature that can distinguish between infectious and non-infectious acute inflammation. It has been validated in multiple cohorts across heterogeneous clinical settings. AIM: To study whether the SMS holds diagnostic validity in determining the etiology of acute arthritis. METHODS: We conducted a blinded, prospective, non-interventional clinical study of the SMS. All patients undergoing work-up for a septic primary joint were enrolled. Patients proceeded through the normal standard-of-care pathway, including joint aspiration and inflammatory labs [white blood cell (WBC), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP)]. Venous blood was also drawn into PAX gene RNA-stabilizing tubes and mRNAs were measured using Nano String nCounter™. SMS was calculated blinded to clinical results. RESULTS: A total of 20 samples were included, of which 11 were infected based on aspiration or intra-operative cultures. The SMS had an area under the ROC curve (AUROC) of 0.87 for separating infectious from non-infectious conditions. For comparison, the AUROCs for ESR = 0.58, CRP = 0.6, and WBC = 0.59. At 100% sensitivity for infection, the specificity of the SMS was 40%, meaning nearly half of non-septic patients could have been ruled out for further intervention. CONCLUSION: In this pilot study, SMS showed a high level of diagnostic accuracy in predicting septic joints compared to other diagnostic biomarkers. This quick blood test could be an important tool for early, accurate identification of acute septic joints and need for emergent surgery, improving clinical care and healthcare spending.

Transcriptome analysis of rhesus monkey failed-to-mature oocytes: deficiencies in transcriptional regulation and cytoplasmic maturation of the oocyte mRNA population.

STUDY QUESTION: Which different pathways and functions are altered in rhesus monkey oocytes that fail to mature after an ovulatory stimulus? SUMMARY ANSWER: Failed to mature (FTM) oocytes complete a large portion of the transition in transcriptome composition associated with normal maturation, but also manifest numerous differences that indicate incomplete transcriptional repression and cytoplasmic maturation affecting multiple processes. WHAT IS KNOWN ALREADY: Oocyte maturation defects contribute to unexplained female infertility. Failure of some oocytes to undergo germinal vesicle breakdown or progress to second meiotic metaphase in response to an ovulatory stimulus can limit the number of high quality oocytes available for ART. STUDY DESIGN, SIZE, DURATION: The transcriptome of rhesus monkey oocytes that failed to mature (FTM; n = 11, 5 donors) in response to an ovulatory stimulus in vivo was compared to those of normal germinal vesicle stage (GV, n = 7, 2 donors) and metaphase II stage (MII, n = 7, 5 donors) oocytes by RNA-sequencing (RNAseq). PARTICIPANTS/MATERIALS, SETTING, METHODS: Female rhesus monkeys of normal breeding age (6-12 years old) and with regular menstrual cycles were used. Animals underwent a controlled ovarian stimulation protocol for the collection of oocytes by ultrasound-guided needle aspiration of follicles. MAIN RESULTS AND THE ROLE OF CHANCE: We obtained a high quality RNAseq dataset consisting of n = 7, n = 7, and n = 11 libraries for normal GV, normal MII and FTM oocytes, respectively. Total reads acquired were an average of 34 million for each GV sample, 41 million for each FTM sample and 59 million for each MII oocyte sample. Approximately 44% of the total reads were exonic reads that successfully aligned to the rhesus monkey genome as unique non-rRNA gene transcript sequences, providing high depth of coverage. Approximately 44% of the mRNAs that undergo changes in abundance during normal maturation display partial modulations to intermediate abundances, and 9.2% fail to diverge significantly from GV stage oocytes. Additionally, a small group of mRNAs are grossly mis-regulated in the FTM oocyte. Differential expression was seen for mRNAs associated with mitochondrial functions, fatty acid beta oxidation, lipid accumulation, meiosis, zona pellucida formation, Hippo pathway signaling, and maternal mRNA regulation. A deficiency DNA methyltransferase one mRNA expression indicates a potential defect in transcriptional silencing. LARGE SCALE DATA: All RNAseq data are published in the Gene Expression Omnibus Database (GSE112536). LIMITATIONS, REASONS FOR CAUTION: These results do not establish cause of maturation failure but reveal novel correlates of incompetence to mature. Transcriptome studies likely do not capture all post-transcriptional or post-translational events that inhibit maturation, but do reveal mRNA expression changes that lie downstream of such events or that are related to effects on upstream regulators. The use of an animal model allows the study of oocyte maturation failure independent of covariates and confounders, such as pre-existing conditions of the female, which is a significant concern in human studies. Depending on the legislation, it may not be possible to collect and study oocytes from healthy women; and using surplus oocytes from patients undergoing ART may introduce confounders that vary from case to case. FTM oocytes were at various stages of meiotic progression, so correlates of specific times of arrest are not revealed. All the FTM oocytes failed to respond appropriately to an ovulatory stimulus in vivo. Therefore, this analysis informs us about common transcriptome features associated with meiotic incompetence. WIDER IMPLICATIONS OF THE FINDINGS: These results reveal that some diagnostic markers of oocyte quality may not reflect developmental competence because even meiotically incompetent oocytes display many normal gene expression features. The results also reveal potential mechanisms by which maternal and environmental factors may impact transcriptional repression and cytoplasmic maturation, and prevent oocyte maturation. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by grants from the National Institutes of Health Office of Research Infrastructure Programs Division of Comparative Medicine Grants R24 [OD012221 to K.E.L., OD011107/RR00169 (California National Primate Research Center), and OD010967/RR025880 to C.A.V.]; the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under the award number T32HD087166; MSU AgBioResearch, Michigan State University. Authors have nothing to disclose.

Novel key roles for structural maintenance of chromosome flexible domain containing 1 (Smchd1) during preimplantation mouse development.

Structural maintenance of chromosome flexible domain containing 1 (Smchd1) is a chromatin regulatory gene for which mutations are associated with facioscapulohumeral muscular dystrophy and arhinia. The contribution of oocyte- and zygote-expressed SMCHD1 to early development was examined in mice ( Mus musculus) using a small interfering RNA knockdown approach. Smchd1 knockdown compromised long-term embryo viability, with reduced embryo nuclear volumes at the morula stage, reduced blastocyst cell number, formation and hatching, and reduced viability to term. RNA sequencing analysis of Smchd1 knockdown morulae revealed aberrant increases in expression of a small number of trophectoderm (TE)-related genes and reduced expression of cell proliferation genes, including S-phase kinase-associated protein 2 ( Skp2). Smchd1 expression was elevated in embryos deficient for Caudal-type homeobox transcription factor 2 ( Cdx2, a key regulator of TE specification), indicating that Smchd1 is normally repressed by CDX2. These results indicate that Smchd1 plays an important role in the preimplantation embryo, regulating early gene expression and contributing to long-term embryo viability. These results extend the known functions of SMCHD1 to the preimplantation period and highlight important function for maternally expressed Smchd1 messenger RNA and protein.

Determination of single embryo sex in Macaca mulatta and Mus musculus RNA-Seq transcriptome profiles.

To account for sex as a biological variable, it is sometimes necessary to identify the sex of an embryo or embryonic cell that was used to generate libraries for RNA sequencing, without the sex being known a priori. The preferred approach for this would take advantage of the mRNA data, rather than relying on other methods that require separation and analysis of genomic DNA or diversion of limiting RNA for other assays. We describe here a method that has been optimized for this purpose in samples of rhesus monkey and mouse embryos. This method is broadly applicable to any species for which a sufficiently well characterized genome and knowledge of polymorphisms are available, and for embryos that are transcriptionally active and expressing their genome.

Changes in gene expression following long-term in vitro exposure of Macaca mulatta trophoblast stem cells to biologically relevant levels of endocrine disruptors.

Trophoblast stem cells (TSCs) are crucial for embryo implantation and placentation. Environmental toxicants that compromise TSC function could impact fetal viability, pregnancy, and progeny health. Understanding the effects of low, chronic EDC exposures on TSCs and pregnancy is a priority in developmental toxicology. Differences in early implantation between primates and other mammals make a nonhuman primate model ideal. We examined effects of chronic low-level exposure to atrazine, tributyltin, bisphenol A, bis(2-ethylhexyl) phthalate, and perfluorooctanoic acid on rhesus monkey TSCs in vitro by RNA sequencing. Pathway analysis of affected genes revealed negative effects on cytokine signaling related to anti-viral response, most strongly for atrazine and tributyltin, but shared with the other three EDCs. Other affected processes included metabolism, DNA repair, and cell migration. Low-level chronic exposure of primate TSCs to EDCs may thus compromise trophoblast development in vivo, inhibit responses to infection, and negatively affect embryo implantation and pregnancy.

TDRD5 binds piRNA precursors and selectively enhances pachytene piRNA processing in mice.

Pachytene piRNAs are the most abundant piRNAs in mammalian adult testes. They are generated from long precursor transcripts by the primary piRNA biogenesis pathway but the factors involved in pachytene piRNA precursors processing are poorly understood. Here we show that the Tudor domain-containing 5 (TDRD5) protein is essential for pachytene piRNA biogenesis in mice. Conditional inactivation of TDRD5 in mouse postnatal germ cells reveals that TDRD5 selectively regulates the production of pachytene piRNAs from abundant piRNA-producing precursors, with little effect on low-abundant piRNAs. Unexpectedly, TDRD5 is not required for the 5' end processing of the precursors, but is crucial for promoting production of piRNAs from the other regions of the transcript. Furthermore, we show that TDRD5 is an RNA-binding protein directly associating with piRNA precursors. These observations establish TDRD5 as a piRNA biogenesis factor and reveal two genetically separable steps at the start of pachytene piRNA processing.

PNLDC1 is essential for piRNA 3' end trimming and transposon silencing during spermatogenesis in mice.

Piwi-interacting RNAs are small regulatory RNAs with key roles in transposon silencing and regulation of gametogenesis. The production of mature piwi-interacting RNAs requires a critical step of trimming piwi-interacting RNA intermediates to achieve optimally sized piwi-interacting RNAs. The poly(A)-specific ribonuclease family deadenylase PNLDC1 is implicated in piwi-interacting RNA trimming in silkworms. The physiological function of PNLDC1 in mammals remains unknown. Using Pnldc1-deficient mice, here we show that PNLDC1 is required for piwi-interacting RNA biogenesis, transposon silencing, and spermatogenesis. Pnldc1 mutation in mice inhibits piwi-interacting RNA trimming and causes accumulation of untrimmed piwi-interacting RNA intermediates with 3' end extension, leading to severe reduction of mature piwi-interacting RNAs in the testis. Pnldc1 mutant mice exhibit disrupted LINE1 retrotransposon silencing and defect in spermiogenesis. Together, these results define PNLDC1 as a mammalian piwi-interacting RNA biogenesis factor that protects the germline genome and ensures normal sperm production in mice.piRNAs are regulatory RNAs that play a critical role in transposon silencing and gametogenesis. Here, the authors provide evidence that mammalian PNLDC1 is a regulator of piRNA biogenesis, transposon silencing and spermatogenesis, protecting the germline genome in mice.

Quantitative assessment of timing, efficiency, specificity and genetic mosaicism of CRISPR/Cas9-mediated gene editing of hemoglobin beta gene in rhesus monkey embryos.

Gene editing technologies offer new options for developing novel biomedical research models and for gene and stem cell based therapies. However, applications in many species demand high efficiencies, specificity, and a thorough understanding of likely editing outcomes. To date, overall efficiencies, rates of off-targeting and degree of genetic mosaicism have not been well-characterized for most species, limiting our ability to optimize methods. As a model gene for measuring these parameters of the CRISPR/Cas9 application in a primate species (rhesus monkey), we selected the ß-hemoglobin gene (HBB), which also has high relevance to the potential application of gene editing and stem-cell technologies for treating human disease. Our data demonstrate an ability to achieve a high efficiency of gene editing in rhesus monkey zygotes, with no detected off-target effects at selected off-target loci. Considerable genetic mosaicism and variation in the fraction of embryonic cells bearing targeted alleles are observed, and the timing of editing events is revealed using a new model. The uses of Cas9-WT protein combined with optimized concentrations of sgRNAs are two likely areas for further refinement to enhance efficiency while limiting unfavorable outcomes that can be exceedingly costly for application of gene editing in primate species.

Effects of long-term endocrine disrupting compound exposure on Macaca mulatta embryonic stem cells.

Endocrine disrupting chemicals (EDCs) exert significant effects on health and physiology, many traceable to effects on stem cell programming underlying development. Understanding risk of low-level, chronic EDC exposure will be enhanced by knowledge of effects on stem cells. We exposed rhesus monkey embryonic stem cells to low levels of five EDCs [bisphenol A (BPA), atrazine (ATR), tributyltin (TBT), perfluorooctanoic acid (PFOA), and di-(2-ethylhexyl) phthalate (DEHP)] for 28days, and evaluated effects on gene expression by RNAseq transcriptome profiling. We observed little effect of BPA, and small numbers of affected genes (≤119) with other EDCs. There was substantial overlap in effects across two, three, or four treatments. Ingenuity Pathway analysis indicated suppression of cell survival genes and genes downstream of several stress response mediators, activation of cell death genes, and modulations in several genes regulating pluripotency, differentiation, and germ layer development. Potential adverse effects of these changes on development are discussed.

Disruptions in follicle cell functions in the ovaries of rhesus monkeys during summer.

Oocytes isolated from female rhesus monkeys following standard ovarian stimulation protocols during the summer months displayed a reduced capacity to mature compared with stimulation during the normal breeding season. Because the gene expression profiles of oocyte-associated cumulus cells and mural granulosa cells (CCs and GCs) are indicative of altered oocyte quality and can provide insight into intrafollicular processes that may be disrupted during oogenesis, we performed array-based transcriptome comparisons of CCs and GCs from summer and normal breeding season stimulation cycles. Summer CCs and GCs both display deficiencies in expression of mRNAs related to cell proliferation, angiogenesis, and endocrine signaling, as well as reduced expression of glycogen phosphorylase. Additionally, CCs display deficiencies in expression of mRNAs related to stress response. These results provide the first insight into the specific molecular pathways and processes that are disrupted in the follicles of rhesus macaque females during the summer season. Some of the changes seen in summer GCs and CCs have been reported in humans and in other model mammalian species. This suggests that the seasonal effects seen in the rhesus monkey may help us to understand better the mechanisms that contribute to reduced oocyte quality and fertility in humans.