Delineating yeast cleavage and polyadenylation signals using deep learning.

3'-end cleavage and polyadenylation is an essential process for eukaryotic mRNA maturation. In yeast species, the polyadenylation signals that recruit the processing machinery are degenerate and remain poorly characterized compared to the well-defined regulatory elements in mammals. Here we address this question by developing deep learning models to deconvolute degenerate cis-regulatory elements and quantify their positional importance in mediating yeast poly(A) site formation, cleavage heterogeneity, and strength. In S. cerevisiae, cleavage heterogeneity is promoted by the depletion of U-rich elements around poly(A) sites as well as multiple occurrences of upstream UA-rich elements. Sites with high cleavage heterogeneity show overall lower strength. The site strength and tandem site distances modulate alternative polyadenylation (APA) under the diauxic stress. Finally, we develop a deep learning model to reveal the distinct motif configuration of S. pombe poly(A) sites, which show more precise cleavage than S. cerevisiae Altogether, our deep learning models provide unprecedented insights into poly(A) site formation of yeast species, and our results highlight divergent poly(A) signals across distantly related species.

Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features.

Studies have revealed dozens of functional peptides in putative 'noncoding' regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the probability that the encoded peptide is stable in humans. Systematic ectopic expression validates PepScore and shows that stable complex-associating microproteins can be encoded in 5'/3' untranslated regions and overlapping coding regions of mRNAs besides annotated noncoding RNAs. Stable noncanonical proteins follow conventional rules and localize to different subcellular compartments. Inhibition of proteasomal/lysosomal degradation pathways can stabilize some peptides especially those with moderate PepScores, but cannot rescue the expression of short ones with low PepScores suggesting they are directly degraded by cellular proteases. The majority of human noncanonical peptides with high PepScores show longer lengths but low conservation across species/mammals, and hundreds contain trait-associated genetic variants. Our study presents a statistical framework to identify stable noncanonical peptides in the genome and provides a valuable resource for functional characterization of noncanonical translation during development and disease.

Deep learning of human polyadenylation sites at nucleotide resolution reveals molecular determinants of site usage and relevance in disease.

The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, spurious polyadenylation can cause premature transcription termination and generate aberrant proteins. To obtain mechanistic insights into polyA site optimization across the human genome, we develop deep/machine learning models to identify genome-wide putative polyA sites at unprecedented nucleotide-level resolution and calculate their strength and usage in the genomic context. Our models quantitatively measure position-specific motif importance and their crosstalk in polyA site formation and cleavage heterogeneity. The intronic site expression is governed by the surrounding splicing landscape. The usage of alternative polyA sites in terminal exons is modulated by their relative locations and distance to downstream genes. Finally, we apply our models to reveal thousands of disease- and trait-associated genetic variants altering polyadenylation activity. Altogether, our models represent a valuable resource to dissect molecular mechanisms mediating genome-wide polyA site expression and characterize their functional roles in human diseases.

Delineating yeast cleavage and polyadenylation signals using deep learning.

3'-end cleavage and polyadenylation is an essential process for eukaryotic mRNA maturation. In yeast species, the polyadenylation signals that recruit the processing machinery are degenerate and remain poorly characterized compared to well-defined regulatory elements in mammals. Especially, recent deep sequencing experiments showed extensive cleavage heterogeneity for some mRNAs in Saccharomyces cerevisiae and uncovered the polyA motif differences between S. cerevisiae vs. Schizosaccharomyces pombe . The findings raised the fundamental question of how polyadenylation signals are formed in yeast. Here we addressed this question by developing deep learning models to deconvolute degenerate cis -regulatory elements and quantify their positional importance in mediating yeast polyA site formation, cleavage heterogeneity, and strength. In S. cerevisiae , cleavage heterogeneity is promoted by the depletion of U-rich elements around polyA sites as well as multiple occurrences of upstream UA-rich elements. Sites with high cleavage heterogeneity show overall lower strength. The site strength and tandem site distances modulate alternative polyadenylation (APA) under the diauxic stress. Finally, we developed a deep learning model to reveal the distinct motif configuration of S. pombe polyA sites which show more precise cleavage than S. cerevisiae . Altogether, our deep learning models provide unprecedented insights into polyA site formation across yeast species.

Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Untangling the heterogeneity of sepsis in children and identifying clinically relevant phenotypes could lead to the development of targeted therapies. Our aim was to analyze the organ dysfunction trajectories of children with sepsis-associated multiple organ dysfunction syndrome (MODS) to identify reproducible and clinically relevant sepsis phenotypes and determine if they are associated with heterogeneity of treatment effect (HTE) to common therapies. DESIGN: Multicenter observational cohort study. SETTING: Thirteen PICUs in the United States. PATIENTS: Patients admitted with suspected infections to the PICU between 2012 and 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used subgraph-augmented nonnegative matrix factorization to identify candidate trajectory-based phenotypes based on the type, severity, and progression of organ dysfunction in the first 72 hours. We analyzed the candidate phenotypes to determine reproducibility as well as prognostic, therapeutic, and biological relevance. Overall, 38,732 children had suspected infection, of which 15,246 (39.4%) had sepsis-associated MODS with an in-hospital mortality of 10.1%. We identified an organ dysfunction trajectory-based phenotype (which we termed persistent hypoxemia, encephalopathy, and shock) that was highly reproducible, had features of systemic inflammation and coagulopathy, and was independently associated with higher mortality. In a propensity score-matched analysis, patients with persistent hypoxemia, encephalopathy, and shock phenotype appeared to have HTE and benefit from adjuvant therapy with hydrocortisone and albumin. When compared with other high-risk clinical syndromes, the persistent hypoxemia, encephalopathy, and shock phenotype only overlapped with 50%-60% of patients with septic shock, moderate-to-severe pediatric acute respiratory distress syndrome, or those in the top tier of organ dysfunction burden, suggesting that it represents a nonsynonymous clinical phenotype of sepsis-associated MODS. CONCLUSIONS: We derived and validated the persistent hypoxemia, encephalopathy, and shock phenotype, which is highly reproducible, clinically relevant, and associated with HTE to common adjuvant therapies in children with sepsis.

Rfoot-seq: Transcriptomic RNase Footprinting for Mapping Stable RNA-Protein Complexes and Rapid Ribosome Profiling.

Ribosome profiling isolates ribosome-protected fragments for sequencing and is a valuable method for studying different aspects of RNA translation. However, conventional protocols require millions of input cells and time-consuming steps to isolate translating ribosome complexes using ultracentrifugation or immunoprecipitation. These limitations have prevented their application to rare physiological samples. To address these technical barriers, we developed an RNase footprinting approach named Rfoot-seq to map stable transcriptomic RNA-protein complexes that allows rapid ribosome profiling using low-input samples (Li, Yang, Stroup, Wang, & Ji, 2022). In this assay, we treat a cell lysate with concentrated RNase without complex crosslinking and retained only RNA footprints associated with stable complexes for sequencing. The footprints in coding regions represent ribosome-protected fragments and can be used to study cytosolic and mitochondrial translation simultaneously. Rfoot-seq achieves comparable results to conventional ribosome profiling to quantify ribosome occupancy and works robustly for various cultured cells and primary tissue samples. Moreover, Rfoot-seq maps RNA fragments associated with stable non-ribosomal RNA-protein complexes in noncoding domains of small noncoding RNAs and some long noncoding RNAs. Taken together, Rfoot-seq opens an avenue to quantify transcriptomic translation and characterize functional noncoding RNA domains using low-input samples. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Harvesting and lysing adherent cells Alternate Protocol 1: Harvesting and lysing suspension cells Alternate Protocol 2: Harvesting and lysing primary tissue samples Basic Protocol 2: RNase treatment and footprint purification for low-input samples Alternate Protocol 3: RNase treatment and footprint purification for ultra-low-input samples Basic Protocol 3: Library preparation for high-throughput sequencing Support Protocol: Preparation of dsDNA markers for library size selection Basic Protocol 4: Data analysis and quality control after sequencing.

Low-input RNase footprinting for simultaneous quantification of cytosolic and mitochondrial translation.

We describe a low-input RNase footprinting approach for the rapid quantification of ribosome-protected fragments with as few as 1000 cultured cells. The assay uses a simplified procedure to selectively capture ribosome footprints based on optimized RNase digestion. It simultaneously maps cytosolic and mitochondrial translation with single-nucleotide resolution. We applied it to reveal selective functions of the elongation factor TUFM in mitochondrial translation, as well as synchronized repression of cytosolic translation after TUFM perturbation. We show the assay is applicable to small amounts of primary tissue samples with low protein synthesis rates, including snap-frozen tissues and immune cells from an individual's blood draw. We showed its feasibility to characterize the personalized immuno-translatome. Our analyses revealed that thousands of genes show lower translation efficiency in monocytes compared with lymphocytes, and identified thousands of translated noncanonical open reading frames (ORFs). Altogether, our RNase footprinting approach opens an avenue to assay transcriptome-wide translation using low-input samples from a wide range of physiological conditions.

CD95/Fas protects triple negative breast cancer from anti-tumor activity of NK cells.

The apoptosis inducing receptor CD95/Fas has multiple tumorigenic activities. In different genetically engineered mouse models tumor-expressed CD95 was shown to be critical for cell growth. Using a combination of immune-deficient and immune-competent mouse models, we now establish that loss of CD95 in metastatic triple negative breast cancer (TNBC) cells prevents tumor growth by modulating the immune landscape. CD95-deficient, but not wild-type, tumors barely grow in an immune-competent environment and show an increase in immune infiltrates into the tumor. This growth reduction is caused by infiltrating NK cells and does not involve T cells or macrophages. In contrast, in immune compromised mice CD95 k.o. cells are not growth inhibited, but they fail to form metastases. In summary, we demonstrate that in addition to its tumor and metastasis promoting activities, CD95 expression by tumor cells can exert immune suppressive activities on NK cells, providing a new target for immune therapy.

Derivation and Validation of Novel Phenotypes of Multiple Organ Dysfunction Syndrome in Critically Ill Children.

Importance: Multiple organ dysfunction syndrome (MODS) is a dynamic and heterogeneous process associated with high morbidity and mortality in critically ill children. Objective: To determine whether data-driven phenotypes of MODS based on the trajectories of 6 organ dysfunctions have prognostic and therapeutic relevance in critically ill children. Design, Setting, and Participants: This cohort study included 20 827 pediatric intensive care encounters among 14 285 children admitted to 2 large academic pediatric intensive care units (PICUs) between January 2010 and August 2016. Patients were excluded if they were older than 21 years or had undergone cardiac surgery. The 6 subscores of the pediatric Sequential Organ Failure Assessment (pSOFA) score were calculated for the first 3 days, including the subscores for respiratory, cardiovascular, coagulation, hepatic, neurologic, and renal dysfunctions. MODS was defined as a pSOFA subscore of at least 2 in at least 2 organs. Encounters were split in a 80:20 ratio for derivation and validation, respectively. The trajectories of the 6 subscores were used to derive a set of data-driven phenotypes of MODS using subgraph-augmented nonnegative matrix factorization in the derivation set. Data analysis was conducted from March to October 2019. Exposures: The primary exposure was phenotype membership. In the subset of patients with vasoactive-dependent shock, the interaction between hydrocortisone and phenotype membership and its association with outcomes were examined in a matched cohort. Main Outcomes and Measures: The primary outcome was in-hospital mortality. Secondary outcomes included persistent MODS on day 7, and vasoactive-free, ventilator-free, and hospital-free days. Regression analysis was used to adjust for age, severity of illness, immunocompromised status, and study site. Results: There were 14 285 patients with 20 827 encounters (median [interquartile range] age 5.2 years [1.5-12.7] years; 11 409 [54.8%; 95% CI, 54.1%-55.5%] male patients). Of these, 5297 encounters (25.4%; 95% CI, 24.8%-26.0%) were with patients who had MODS, of which 5054 (95.4%) met the subgraph count threshold and were included in the analysis. Subgraph augmented nonnegative matrix factorization uncovered 4 data-driven phenotypes of MODS, characterized by a combination of neurologic, respiratory, coagulation, and cardiovascular dysfunction, as follows: phenotype 1, severe, persistent encephalopathy (1019 patients [19.2%]); phenotype 2, moderate, resolving hypoxemia (1828 patients [34.5%]); phenotype 3, severe, persistent hypoxemia and shock (1012 patients [19.1%]); and phenotype 4, moderate, persistent thrombocytopenia and shock (1195 patients [22.6%]). These phenotypes were reproducible in a validation set of encounters, had distinct clinical characteristics, and were independently associated with outcomes. For example, using phenotype 2 as reference, the adjusted hazard ratios (aHRs) for death by 28 days were as follows: phenotype 1, aHR of 3.0 (IQR, 2.1-4.3); phenotype 3, aHR of 2.8 (IQR, 2.0-4.1); and phenotype 4, aHR of 1.8 (IQR, 1.2-2.6). Interaction analysis in a matched cohort of patients with vasoactive-dependent shock revealed that hydrocortisone had differential treatment association with vasoactive-free days across phenotypes. For example, patients in phenotype 3 who received hydrocortisone had more vasoactive-free days than those who did not (23 days vs 18 days; P for interaction < .001), whereas patients in other phenotypes who received hydrocortisone either had no difference or had less vasoactive-free days. Conclusions and Relevance: In this study, data-driven phenotyping in critically ill children with MODS uncovered 4 distinct and reproducible phenotypes with prognostic relevance and possible therapeutic relevance. Further validation and characterization of these phenotypes is warranted.

Genome-wide mapping of 5-hydroxymethylcytosines in circulating cell-free DNA as a non-invasive approach for early detection of hepatocellular carcinoma.

OBJECTIVE: The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC). We sought to develop a non-invasive diagnostic approach using circulating cell-free DNA (cfDNA) for the early detection of HCC. DESIGN: Applying the 5hmC-Seal technique, we obtained genome-wide 5-hydroxymethylcytosines (5hmC) in cfDNA samples from 2554 Chinese subjects: 1204 patients with HCC, 392 patients with chronic hepatitis B virus infection (CHB) or liver cirrhosis (LC) and 958 healthy individuals and patients with benign liver lesions. A diagnostic model for early HCC was developed through case-control analyses using the elastic net regularisation for feature selection. RESULTS: The 5hmC-Seal data from patients with HCC showed a genome-wide distribution enriched with liver-derived enhancer marks. We developed a 32-gene diagnostic model that accurately distinguished early HCC (stage 0/A) based on the Barcelona Clinic Liver Cancer staging system from non-HCC (validation set: area under curve (AUC)=88.4%; (95% CI 85.8% to 91.1%)), showing superior performance over α-fetoprotein (AFP). Besides detecting patients with early stage or small tumours (eg, ≤2.0 cm) from non-HCC, the 5hmC model showed high capacity for distinguishing early HCC from high risk subjects with CHB or LC history (validation set: AUC=84.6%; (95% CI 80.6% to 88.7%)), also significantly outperforming AFP. Furthermore, the 5hmC diagnostic model appeared to be independent from potential confounders (eg, smoking/alcohol intake history). CONCLUSION: We have developed and validated a non-invasive approach with clinical application potential for the early detection of HCC that are still surgically resectable in high risk individuals.

Towards precision medicine: advances in 5-hydroxymethylcytosine cancer biomarker discovery in liquid biopsy.

Robust and clinically convenient biomarkers for cancer diagnosis, early detection, and prognosis have great potential to improve patient survival and are the key to precision medicine. The advent of next-generation sequencing technologies enables a more sensitive and comprehensive profiling of genetic and epigenetic information in tumor-derived materials. Researchers are now able to monitor the dynamics of tumorigenesis in new dimensions, such as using circulating cell-free DNA (cfDNA) and tumor DNA (ctDNA). Mutation-based assays in liquid biopsy cannot always provide consistent results across studies due partly to intra- and inter-tumoral heterogeneity as well as technical limitations. In contrast, epigenetic analysis of patient-derived cfDNA is a promising alternative, especially for early detection and disease surveillance, because epigenetic modifications are tissue-specific and reflect the dynamic process of cancer progression. Therefore, cfDNA-based epigenetic assays are emerging to be a highly sensitive, minimally invasive tool for cancer diagnosis and prognosis with great potential in future precise care of cancer patients. The major obstacle for applying epigenetic analysis of cfDNA, however, has been the lack of enabling techniques with high sensitivity and technical robustness. In this review, we summarized the advances in epigenome-wide profiling of 5-hydroxymethylcytosine (5hmC) in cfDNA, focusing on the detection approaches and potential role as biomarkers in different cancer types.

Phenotyping Multiple Organ Dysfunction Syndrome Using Temporal Trends in Critically Ill Children.

Multiple organ dysfunction syndrome (MODS) is one of the most common causes of death in critically ill children. However, despite decades of clinical trials, there are no comprehensive approaches to the management of MODS or effective targeted therapies that have consistently improved outcomes. Better understanding the heterogeneity of MODS and characterizing subgroups of MODS patients could improve our understanding of the syndrome and help us develop new management strategies. We analyzed a cohort of 5,297 children with MODS from two children's hospitals and used subgraph-augmented non-negative matrix factorization (SANMF) to identify unique temporal patterns in organ dysfunction across four novel subgroups. We demonstrate that these subgroups are composed of patients with distinct clinical characteristics and are independently predictive of clinical outcomes. Our work suggests that these subgroups represent four relevant phenotypes of pediatric MODS that could be used to identify novel management strategies.

Mutations in microRNA processing genes in Wilms tumors derepress the IGF2 regulator PLAG1.

Many childhood Wilms tumors are driven by mutations in the microRNA biogenesis machinery, but the mechanism by which these mutations drive tumorigenesis is unknown. Here we show that the transcription factor pleomorphic adenoma gene 1 (PLAG1) is a microRNA target gene that is overexpressed in Wilms tumors with mutations in microRNA processing genes. Wilms tumors can also overexpress PLAG1 through copy number alterations, and PLAG1 expression correlates with prognosis in Wilms tumors. PLAG1 overexpression accelerates growth of Wilms tumor cells in vitro and induces neoplastic growth in the developing mouse kidney in vivo. In both settings, PLAG1 transactivates insulin-like growth factor 2 (IGF2), a key Wilms tumor oncogene, and drives mammalian target of rapamycin complex 1 (mTORC1) signaling. These data link microRNA impairment to the PLAG1-IGF2 pathway, providing new insight into the manner in which common Wilms tumor mutations drive disease pathogenesis.

EGF Receptor and mTORC1 Are Novel Therapeutic Targets in Nonseminomatous Germ Cell Tumors.

Germ cell tumors (GCT) are malignant tumors that arise from pluripotent embryonic germ cells and occur in children and young adults. GCTs are treated with cisplatin-based regimens which, while overall effective, fail to cure all patients and cause significant adverse late effects. The seminoma and nonseminoma forms of GCT exhibit distinct differentiation states, clinical behavior, and response to treatment; however, the molecular mechanisms of GCT differentiation are not fully understood. We tested whether the activity of the mTORC1 and MAPK pathways were differentially active in the two classes of GCT. Here we show that nonseminomatous germ cell tumors (NSGCT, including embryonal carcinoma, yolk sac tumor, and choriocarcinoma) from both children and adults display activation of the mTORC1 pathway, while seminomas do not. In seminomas, high levels of REDD1 may negatively regulate mTORC1 activity. In NSGCTs, on the other hand, EGF and FGF2 ligands can stimulate mTORC1 and MAPK signaling, and members of the EGF and FGF receptor families are more highly expressed. Finally, proliferation of NSGCT cells in vitro and in vivo is significantly inhibited by combined treatment with the clinically available agents erlotinib and rapamycin, which target EGFR and mTORC1 signaling, respectively. These results provide an understanding of the signaling network that drives GCT growth and a rationale for therapeutic targeting of GCTs with agents that antagonize the EGFR and mTORC1 pathways. Mol Cancer Ther; 17(5); 1079-89. ©2018 AACR.

The multicomponent medication lymphomyosot improves the outcome of experimental lymphedema.

BACKGROUND: Secondary lymphedema is a life-long disease of painful tissue swelling that often follows axillary lymph node dissection to treat breast cancer. It is hypothesized that poor lymphatic regeneration across the obstructive scar tissue during the wound healing process may predispose the tissue to swell at a later date. Treatment for lymphedema remains suboptimal and is in most cases palliative. The purpose of this study was to evaluate the ability of Lymphomyosot to treat tissue swelling and promote lymphangiogenesis in experimental models of murine lymphedema. METHODS: Experimental models of mouse lymphedema were injected with varied amounts of Lymphomyosot and saline as control. Measurements of tail swelling and wound closure were taken and compared amongst the groups. Three separate groups of mice were analyzed for lymphatic capillary migration, lymphatic vessel regeneration, and macrophage recruitment. RESULTS: Lymphomyosot significantly reduced swelling and increased the rate of surgical wound closure. Lymphomyosot did not increase the migration of lymph capillaries in a mouse tail skin regeneration model or regeneration of lymph vessels following murine axillary lymph node dissection. CONCLUSIONS: Lymphomyosot may act through inflammatory and wound repair pathways to reduce experimental lymphedema. Its ability to regulate inflammation as well as assist in tissue repair and extracellular formation may allow for the production of a scar-free matrix bridge through which migrating cells and accumulated interstitial fluid can freely spread.

A chronic and latent lymphatic insufficiency follows recovery from acute lymphedema in the rat foreleg.

Secondary lymphedema in humans is a common consequence of axillary lymph node dissection (ALND) to treat breast cancer. Remarkably, secondary lymphedema generally first appears following a delay of over a year and can be triggered suddenly by an inflammatory insult. However, it remains unclear why the apparently functional lymphatic system is unable to accommodate an inflammatory trigger. To provide mechanistic insight into the delayed and rapid secondary lymphedema initiation, we compared the ability of the ALND-recovered rat foreleg lymphatic system to prevent edema during an inflammatory challenge with that of the uninjured lymphatic system. At 73 days postsurgery, the forelegs of ALND(-)- and ALND(+)-sensitized rats were exposed to the proinflammatory agent oxazolone, which was found to reduce fluid drainage and increase skin thickness in both ALND(-) and ALND(+) forelegs (P < 0.05). However, drainage in the ALND-recovered forelegs was more severely impaired than ALND(-) forelegs, as visualized by indocyanine green lymphography and quantified by interstitial transport of fluid marker (P < 0.05). Although both ALND(+) and ALND(-) forelegs experienced significant inflammation-induced edema with the oxazolone exposure (P < 0.05), the peak tissue swelling in the ALND(+) group was significantly greater than that of the ALND(-) forelegs (arm area peaked at ∼13.4 vs. ∼5.7% swelling, respectively, P < 0.005; wrist diameter peaked at 9.7 vs. 2.2% swelling, respectively, P < 0.005). The findings demonstrate that outward recovery from ALND in the rat foreleg masks an ensuing chronic and latent lymphatic insufficiency, which reduces the ability of the foreleg lymphatic system to prevent edema during an acute inflammatory process.