De novo gene synthesis by an antiviral reverse transcriptase.

Bacteria defend themselves from viral infection using diverse immune systems, many of which sense and target foreign nucleic acids. Defense-associated reverse transcriptase (DRT) systems provide an intriguing counterpoint to this immune strategy by instead leveraging DNA synthesis, but the identities and functions of their DNA products remain largely unknown. Here we show that DRT2 systems execute an unprecedented immunity mechanism that involves de novo gene synthesis via rolling-circle reverse transcription of a non-coding RNA (ncRNA). Unbiased profiling of RT-associated RNA and DNA ligands in DRT2-expressing cells revealed that reverse transcription generates concatenated cDNA repeats through programmed template jumping on the ncRNA. The presence of phage then triggers second-strand cDNA synthesis, leading to the production of long double-stranded DNA. Remarkably, this DNA product is efficiently transcribed, generating messenger RNAs that encode a stop codon-less, never-ending ORF (neo) whose translation causes potent growth arrest. Phylogenetic analyses and screening of diverse DRT2 homologs further revealed broad conservation of rolling-circle reverse transcription and Neo protein function. Our work highlights an elegant expansion of genome coding potential through RNA-templated gene creation, and challenges conventional paradigms of genetic information encoded along the one-dimensional axis of genomic DNA.

Incidence, epidemiology, and outcomes of acute allograft rejection following liver transplantation in Australia.

Acute allograft rejection is a well-known complication of liver transplantation (LT). The incidence, epidemiology, and outcomes of acute rejection have not been well described in Australia. We retrospectively studied consecutive adults who underwent deceased donor LT at a single center between 2010 and 2020. Donor and recipient data at the time of LT and recipient outcomes were collected from a prospective LT database. Liver biopsy reports were reviewed, and only a graft's first instance of biopsy-proven acute rejection was analyzed. During the study period, 796 liver transplants were performed in 770 patients. Biopsy-proven rejection occurred in 34.9% of transplants. There were no significant changes in the incidence of rejection over time (linear trend p =0.11). The median time to the first episode of rejection was 71 days after LT: 2.2% hyperacute, 50.4% early (≤90 d), and 47.5% late rejection (>90 d). Independent risk factors for rejection were younger recipient age at transplant (aHR 0.98 per year increase, 95% CI: 0.97-1.00, p =0.01), and ABO-incompatible grafts (aHR 2.55 vs. ABO-compatible, 95% CI: 1.27-5.09, p <0.01) while simultaneous multiorgan transplants were protective (aHR 0.21 vs. LT only, 95% CI: 0.08-0.58, p <0.01). Development of acute rejection (both early and late) was independently associated with significantly reduced graft (aHR 3.13, 95% CI: 2.21-4.42, p <0.001) and patient survival (aHR 3.42, 95% CI: 2.35-4.98, p <0.001). In this 11-year Australian study, acute LT rejection occurred in 35%, with independent risk factors of younger recipient age and ABO-incompatible transplant, while having a simultaneous multiorgan transplant was protective. Acute rejection was independently associated with reduced graft and patient survival after adjustment for other factors.

Uncovering Distinct Peptide Charging Behaviors in Electrospray Ionization Mass Spectrometry Using a Large-Scale Dataset.

Electrospray ionization is a powerful and prevalent technique used to ionize analytes in mass spectrometry. The distribution of charges that an analyte receives (charge state distribution, CSD) is an important consideration for interpreting mass spectra. However, due to an incomplete understanding of the ionization mechanism, the analyte properties that influence CSDs are not fully understood. Here, we employ a machine learning-based approach and analyze CSDs of hundreds of thousands of peptides. Interestingly, half of the peptides exhibit charges that differ from what one would naively expect (the number of basic sites). We find that these peptides can be classified into two regimes (undercharging and overcharging) and that these two regimes display markedly different charging characteristics. Notably, peptides in the overcharging regime show minimal dependence on basic site count, and more generally, the two regimes exhibit distinct sequence determinants. These findings highlight the rich ionization behavior of peptides and the potential of CSDs for enhancing peptide identification.

Assembly and function of the amyloid-like translational repressor Rim4 is coupled with nutrient conditions.

Amyloid-like protein assemblies have been associated with toxic phenotypes because of their repetitive and stable structure. However, evidence that cells exploit these structures to control function and activity of some proteins in response to stimuli has questioned this paradigm. How amyloid-like assembly can confer emergent functions and how cells couple assembly with environmental conditions remains unclear. Here, we study Rim4, an RNA-binding protein that forms translation-repressing assemblies during yeast meiosis. We demonstrate that in its assembled and repressive state, Rim4 binds RNA more efficiently than in its monomeric and idle state, revealing a causal connection between assembly and function. The Rim4-binding site location within the transcript dictates whether the assemblies can repress translation, underscoring the importance of the architecture of this RNA-protein structure for function. Rim4 assembly depends exclusively on its intrinsically disordered region and is prevented by the Ras/protein kinase A signaling pathway, which promotes growth and suppresses meiotic entry in yeast. Our results suggest a mechanism whereby cells couple a functional protein assembly with a stimulus to enforce a cell fate decision.

A high-throughput approach reveals distinct peptide charging behaviors in electrospray ionization mass spectrometry.

Electrospray ionization is a powerful and prevalent technique used to ionize analytes in mass spectrometry. The distribution of charges that an analyte receives (charge state distribution, CSD) is an important consideration for interpreting mass spectra. However, due to an incomplete understanding of the ionization mechanism, the analyte properties that influence CSDs are not fully understood. Here, we employ a machine learning-based high-throughput approach and analyze CSDs of hundreds of thousands of peptides. Interestingly, half of the peptides exhibit charges that differ from what one would naively expect (number of basic sites). We find that these peptides can be classified into two regimes-undercharging and overcharging-and that these two regimes display markedly different charging characteristics. Strikingly, peptides in the overcharging regime show minimal dependence on basic site count, and more generally, the two regimes exhibit distinct sequence determinants. These findings highlight the rich ionization behavior of peptides and the potential of CSDs for enhancing peptide identification.

Banff 2016 Global Assessment and Quantitative Scoring for T Cell-Mediated Liver Transplant Rejection are Interchangeable.

Introduction: Histopathological assessment of liver biopsies is the current "gold standard" for diagnosing graft dysfunction after liver transplantation (LT), as graft dysfunction can have nonspecific clinical presentations and inconsistent patterns of liver biochemical dysfunction. Most commonly, post-LT, graft dysfunction within the first year, is due to acute T-cell mediated rejection (TCMR) which is characterised histologically by the degree of portal inflammation (PI), bile duct damage (BDD), and venous endothelial inflammation (VEI). This study aimed to establish the relationship between global assessment, which is the global grading of rejection using a "gestalt" approach, and the rejection activity index (RAI) of each component of TCMR as described in revised Banff 2016 guidelines. Methods: Liver biopsies (n = 90) taken from patients who underwent LT in 2015 and 2016 at the Australian National Liver Transplant Unit were identified from the electronic medical records. All biopsy slides were microscopically graded by at least two assessors independently using the revised 2016 Banff criteria. Data were analysed using IBM SPSS v21. A Fisher-Freeman-Halton test was performed to assess the correlation between the global assessment and the RAI scores for each TCMR biopsy. Results: Within the cohort, 60 (37%, n = 164) patients underwent at least 1 biopsy within 12 months after LT. The most common biopsy outcome (total n = 90) was acute TCMR (64, 71.1%). Global assessment of TCMR slides strongly positively correlated with PI (p value <0.001), BDD (p value <0.001), VEI (p value <0.001), and total RAI (p value <0.001). Liver biochemistry of patients with TCMR significantly improved within 4 to 6 weeks post-biopsy compared to the day of the biopsy. Conclusion: In acute TCMR, global assessment and total RAI are strongly correlated and can be used interchangeably to describe the severity of TCMR.

Mapping the Chemical Space of Active-Site Targeted Covalent Ligands for Protein Tyrosine Phosphatases.

Protein tyrosine phosphatases (PTPs) are an important class of enzymes that modulate essential cellular processes through protein dephosphorylation and are dysregulated in various disease states. There is demand for new compounds that target the active sites of these enzymes, for use as chemical tools to dissect their biological roles or as leads for the development of new therapeutics. In this study, we explore an array of electrophiles and fragment scaffolds to investigate the required chemical parameters for covalent inhibition of tyrosine phosphatases. Our analysis juxtaposes the intrinsic electrophilicity of these compounds with their potency against several classical PTPs, revealing chemotypes that inhibit tyrosine phosphatases while minimizing excessive, potentially non-specific reactivity. We also assess sequence divergence at key residues in PTPs to explain their differential susceptibility to covalent inhibition. We anticipate that our study will inspire new strategies to develop covalent probes and inhibitors for tyrosine phosphatases.

Alternative polyadenylation alters protein dosage by switching between intronic and 3'UTR sites.

Alternative polyadenylation (APA) creates distinct transcripts from the same gene by cleaving the pre-mRNA at poly(A) sites that can lie within the 3' untranslated region (3'UTR), introns, or exons. Most studies focus on APA within the 3'UTR; however, here, we show that CPSF6 insufficiency alters protein levels and causes a developmental syndrome by deregulating APA throughout the transcript. In neonatal humans and zebrafish larvae, CPSF6 insufficiency shifts poly(A) site usage between the 3'UTR and internal sites in a pathway-specific manner. Genes associated with neuronal function undergo mostly intronic APA, reducing their expression, while genes associated with heart and skeletal function mostly undergo 3'UTR APA and are up-regulated. This suggests that, under healthy conditions, cells toggle between internal and 3'UTR APA to modulate protein expression.

SEC-TMT facilitates quantitative differential analysis of protein interaction networks.

The majority of cellular proteins interact with at least one partner or assemble into molecular-complexes to exert their function. This network of protein-protein interactions (PPIs) and the composition of macromolecular machines differ between cell types and physiological conditions. Therefore, characterizing PPI networks and their dynamic changes is vital for discovering novel biological functions and underlying mechanisms of cellular processes. However, producing an in-depth, global snapshot of PPIs from a given specimen requires measuring tens to thousands of LC-MS/MS runs. Consequently, while recent works made seminal contributions by mapping PPIs at great depth, almost all focused on just 1-2 conditions, generating comprehensive but mostly static PPI networks. In this study we report the development of SEC-TMT, a method that enables identifying and measuring PPIs in a quantitative manner from only 4-8 LC-MS/MS runs per biological sample. This was accomplished by incorporating tandem mass tag (TMT) multiplexing with a size exclusion chromatography mass spectrometry (SEC-MS) work-flow. SEC-TMT reduces measurement time by an order of magnitude while maintaining resolution and coverage of thousands of cellular interactions, equivalent to the gold standard in the field. We show that SEC-TMT provides benefits for conducting differential analyses to measure changes in the PPI network between conditions. This development makes it feasible to study dynamic systems at scale and holds the potential to drive more rapid discoveries of PPI impact on cellular processes.

Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Proteomics, Post-translational Modifications, and Integrative Analyses Reveal Molecular Heterogeneity within Medulloblastoma Subgroups.

There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven cells to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for future therapeutic strategies.

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 µg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Analysis of spatiotemporal pattern and quantification of gastrointestinal slow waves caused by anticholinergic drugs.

Anticholinergic drugs are well-known to cause adverse effects, such as constipation, but their effects on baseline contractile activity in the gut driven by slow waves is not well established. In a video-based gastrointestinal motility monitoring (GIMM) system, a mouse's small intestine was placed in Krebs solution and recorded using a high definition camera. Untreated controls were recorded for each specimen, then treated with a therapeutic concentration of the drug, and finally, treated with a supratherapeutic dose of the drug. Next, the video clips showing gastrointestinal motility were processed, giving us the segmentation motions of the intestine, which were then converted via Fast Fourier Transform (FFT) into their respective frequency spectrums. These contraction quantifications were analyzed from the video recordings under standardised conditions to evaluate the effect of drugs. Six experimental trials were included with benztropine and promethazine treatments. Only the supratherapeutic dose of benztropine was shown to significantly decrease the amplitude of contractions; at therapeutic doses of both drugs, neither frequency nor amplitude was significantly affected. We have demonstrated that intestinal slow waves can be analyzed based on the colonic frequency or amplitude at a supratherapeutic dose of the anticholinergic medications. More research is required on the effects of anticholinergic drugs on these slow waves to ascertain the true role of ICC in neurologic control of gastrointestinal motility.