VISTA is a potent negative regulator of T cell function that is expressed on hematopoietic cells and leukocytes. VISTA levels are heightened within the tumor microenvironment where its blockade can enhance anti-tumor immune responses in mice. In humans, blockade of the related PD-1 pathway has shown great potential in clinical immunotherapy trials. Here we report the structure of human VISTA and examine its function in lymphocyte negative regulation in cancer. VISTA is expressed predominantly within the hematopoietic compartment with highest expression within the myeloid lineage. VISTA-Ig suppressed proliferation of T cells but not B cells, blunted production of T cell cytokines and activation markers. Our results establish VISTA as a negative checkpoint regulator that suppresses T cell activation, induces Foxp3 expression and is highly expressed within the tumor microenvironment. By analogy to PD-1 and PD-L1 blockade, VISTA blockade may offer an immunotherapeutic strategy for human cancer.

For over fifty years, the methylation of mammalian actin at histidine 73 (actin-H73me) has been known to exist 1 . Beyond mammals, we find that actin-H73me is conserved in several additional model animal and plant organisms. Despite the pervasiveness of H73me, its function is enigmatic, and the enzyme generating this modification is unknown. Here, we identify SETD3 ( SET d omain protein 3 ) as the physiologic actin histidine 73 methyltransferase. Structural studies reveal that an extensive network of interactions clamps the actin peptide on the SETD3 surface to properly orient H73 within the catalytic pocket and facilitate methyl transfer. H73me reduces the nucleotide exchange rate on actin monomers and modestly accelerates actin filament assembly. Mice lacking SETD3 show complete loss of actin-H73me in multiple tissues and quantitative proteomics singles out actin-H73 as the principal physiologic SETD3 substrate. SETD3 deficient female mice have severely decreased litter sizes due to primary maternal dystocia that is refractory to ecbolic induction agents. Further, depletion of SETD3 impairs signal-induced contraction in primary human uterine smooth muscle cells. Together, our results identify the first mammalian protein histidine methyltransferase and uncover a pivotal role for SETD3 and actin-H73me in the regulation of smooth muscle contractility. Our data also support the broader hypothesis where protein histidine methylation acts as a common regulatory mechanism.

Substrate derived biomarkers are necessary in slowly progressing monogenetic diseases caused by single enzyme deficiencies to identify affected patients and serve as surrogate markers for therapy response. N-glycanase 1 (NGLY1) deficiency is an ultra-rare autosomal recessive disorder characterized by developmental delay, peripheral neuropathy, elevated liver transaminases, hyperkinetic movement disorder, and (hypo)-alacrima. We demonstrate that N-acetylglucosamine-asparagine (GlcNAc-Asn; GNA), is the analyte most closely associated with NGLY1 deficiency, showing consistent separation in levels between patients and controls. GNA accumulation is directly linked to the absence of functional NGLY1, presenting strong potential for its use as a biomarker. In agreement, a quantitative LC-MS/MS assay, developed to assess GNA from 3 to 3000 ng/mL, showed it is conserved as a marker for loss of NGLY1 function in NGLY1 deficient cell lines, rodents (urine, cerebrospinal fluid, plasma, and tissues), and patients (plasma and urine). Elevated GNA levels differentiate patients from controls, are stable over time, and correlate with changes in NGLY1 activity. GNA as a biomarker has the potential to identify and validate patients with NGLY1 deficiency, act as a direct pharmacodynamic marker, and serve as a potential surrogate endpoint in clinical trials.

Background Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting respiratory epithelial cells. We investigated the use of liquid chromatography quadrupole time-of-flight mass spectrometry (LC/Q-TOF) combined with machine learning for the diagnosis of influenza infection. Methods We analyzed nasopharyngeal swab samples by LC/Q-TOF to identify distinct metabolic signatures for diagnosis of acute illness. Machine learning models were performed for classification, followed by Shapley additive explanation (SHAP) analysis to analyze feature importance and for biomarker discovery. Findings A total of 236 samples were tested in the discovery phase by LC/Q-TOF, including 118 positive samples (40 influenza A 2009 H1N1, 39 influenza H3 and 39 influenza B) as well as 118 age and sex-matched negative controls with acute respiratory illness. Analysis showed an area under the receiver operating characteristic curve (AUC) of 1.00 (95% confidence interval [95% CI] 0.99, 1.00), sensitivity of 1.00 (95% CI 0.86, 1.00) and specificity of 0.96 (95% CI 0.81, 0.99). The metabolite most strongly associated with differential classification was pyroglutamic acid. Independent validation of a biomarker signature based on the top 20 differentiating ion features was performed in a prospective cohort of 96 symptomatic individuals including 48 positive samples (24 influenza A 2009 H1N1, 5 influenza H3 and 19 influenza B) and 48 negative samples. Testing performed using a clinically-applicable targeted approach, liquid chromatography triple quadrupole mass spectrometry, showed an AUC of 1.00 (95% CI 0.998, 1.00), sensitivity of 0.94 (95% CI 0.83, 0.98), and specificity of 1.00 (95% CI 0.93, 1.00). Limitations include lack of sample suitability assessment, and need to validate these findings in additional patient populations. Interpretation This metabolomic approach has potential for diagnostic applications in infectious diseases testing, including other respiratory viruses, and may eventually be adapted for point-of-care testing.

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