Correcting PCR amplification errors in unique molecular identifiers to generate accurate numbers of sequencing molecules.

Unique molecular identifiers are random oligonucleotide sequences that remove PCR amplification biases. However, the impact that PCR associated sequencing errors have on the accuracy of generating absolute counts of RNA molecules is underappreciated. We show that PCR errors are a source of inaccuracy in both bulk and single-cell sequencing data, and synthesizing unique molecular identifiers using homotrimeric nucleotide blocks provides an error-correcting solution that allows absolute counting of sequenced molecules.

Single nucleus and spatial transcriptomic profiling of healthy human hamstring tendon.

The molecular and cellular basis of health in human tendons remains poorly understood. Among human tendons, hamstring tendon has markedly low pathology and can provide a prototypic healthy tendon reference. The aim of this study was to determine the transcriptomes and location of all cell types in healthy hamstring tendon. Using single nucleus RNA sequencing, we profiled the transcriptomes of 10 533 nuclei from four healthy donors and identified 12 distinct cell types. We confirmed the presence of two fibroblast cell types, endothelial cells, mural cells, and immune cells, and identified cell types previously unreported in tendons, including different skeletal muscle cell types, satellite cells, adipocytes, and undefined nervous system cells. The location of these cell types within tendon was defined using spatial transcriptomics and imaging, and potential transcriptional networks and cell-cell interactions were analyzed. We demonstrate that fibroblasts have the highest number of potential cell-cell interactions in our dataset, are present throughout the tendon, and play an important role in the production and organization of extracellular matrix, thus confirming their role as key regulators of hamstring tendon homeostasis. Overall, our findings underscore the complexity of the cellular networks that underpin healthy human tendon function and the central role of fibroblasts as key regulators of hamstring tendon tissue homeostasis.

PLMC: Language Model of Protein Sequences Enhances Protein Crystallization Prediction.

X-ray diffraction crystallography has been most widely used for protein three-dimensional (3D) structure determination for which whether proteins are crystallizable is a central prerequisite. Yet, there are a number of procedures during protein crystallization, including protein material production, purification, and crystal production, which take turns affecting the crystallization outcome. Due to the expensive and laborious nature of this multi-stage process, various computational tools have been developed to predict protein crystallization propensity, which is then used to guide the experimental determination. In this study, we presented a novel deep learning framework, PLMC, to improve multi-stage protein crystallization propensity prediction by leveraging a pre-trained protein language model. To effectively train PLMC, two groups of features of each protein were integrated into a more comprehensive representation, including protein language embeddings from the large-scale protein sequence database and a handcrafted feature set consisting of physicochemical, sequence-based and disordered-related information. These features were further separately embedded for refinement, and then concatenated for the final prediction. Notably, our extensive benchmarking tests demonstrate that PLMC greatly outperforms other state-of-the-art methods by achieving AUC scores of 0.773, 0.893, and 0.913, respectively, at the aforementioned individual stages, and 0.982 at the final crystallization stage. Furthermore, PLMC is shown to be superior for predicting the crystallization of both globular and membrane proteins, as demonstrated by an AUC score of 0.991 for the latter. These results suggest the significant potential of PLMC in assisting researchers with the experimental design of crystallizable protein variants.

Overcoming barriers to single-cell RNA sequencing adoption in low- and middle-income countries.

The advent of single-cell resolution sequencing and spatial transcriptomics has enabled the delivery of cellular and molecular atlases of tissues and organs, providing new insights into tissue health and disease. However, if the full potential of these technologies is to be equitably realised, ancestrally inclusivity is paramount. Such a goal requires greater inclusion of both researchers and donors in low- and middle-income countries (LMICs). In this perspective, we describe the current landscape of ancestral inclusivity in genomic and single-cell transcriptomic studies. We discuss the collaborative efforts needed to scale the barriers to establishing, expanding, and adopting single-cell sequencing research in LMICs and to enable globally impactful outcomes of these technologies.

MicroRNA analysis of medium/large placenta extracellular vesicles in normal and preeclampsia pregnancies.

Background: Preeclampsia (PE) is a hypertensive disorder of pregnancy, affecting 2%-8% of pregnancies worldwide, and is the leading cause of adverse maternal and fetal outcomes. The disease is characterized by oxidative and cellular stress and widespread endothelial dysfunction. While the precise mechanisms are not entirely understood, the pathogenesis of PE is closely linked to placental dysfunction and, to some extent, syncytiotrophoblast extracellular vesicle release (STB-EVs). These vesicles can be divided into the less well-studied medium/large EVs (220-1,000 nm) released in response to stress and small EVs (<220 nm) released as a component of intercellular communication. The previously described production of m/lSTB-EVs in response to cellular stress combined with the overwhelming occurrence of cellular and oxidative stress in PE prompted us to evaluate the microRNAome of PE m/lSTB-EVs. We hypothesized that the microRNAome profile of m/lSTB-EVs is different in PE compared to normal pregnancy (NP), which might permit the identification of potential circulating biomarkers not previously described in PE. Methods/study design: We performed small RNA sequencing on medium/large STB-EVs isolated from PE and NP placentae using dual-lobe ex vivo perfusion. The sequencing data was bioinformatically analyzed to identify differentially regulated microRNAs. Identified microRNAs were validated with quantitative PCR analysis. We completed our analysis by performing an in-silico prediction of STB-EV mechanistic pathways. Results: We identified significant differences between PE and NP in the STB-EVs micro ribonucleic acid (microRNA) profiles. We verified the differential expression of hsa-miR-193b-5p, hsa-miR-324-5p, hsa-miR-652-3p, hsa-miR-3196, hsa-miR-9-5p, hsa-miR-421, and hsa-miR-210-3p in the medium/large STB-EVs. We also confirmed the differential abundance of hsa-miR-9-5p in maternal serum extracellular vesicles (S EVs). In addition, we integrated the results of these microRNAs into the previously published messenger RNA (mRNA) data to better understand the relationship between these biomolecules. Conclusions: We identified a differentially regulated micro-RNA, hsa-miR-9-5p, that may have biomarker potential and uncovered mechanistic pathways that may be important in the pathophysiology of PE.

Iberdomide increases innate and adaptive immune cell subsets in the bone marrow of patients with relapsed/refractory multiple myeloma.

Iberdomide is a potent cereblon E3 ligase modulator (CELMoD agent) with promising efficacy and safety as a monotherapy or in combination with other therapies in patients with relapsed/refractory multiple myeloma (RRMM). Using a custom mass cytometry panel designed for large-scale immunophenotyping of the bone marrow tumor microenvironment (TME), we demonstrate significant increases of effector T and natural killer (NK) cells in a cohort of 93 patients with multiple myeloma (MM) treated with iberdomide, correlating findings to disease characteristics, prior therapy, and a peripheral blood immune phenotype. Notably, changes are dose dependent, associated with objective response, and independent of prior refractoriness to MM therapies. This suggests that iberdomide broadly induces innate and adaptive immune activation in the TME, contributing to its antitumor efficacy. Our approach establishes a strategy to study treatment-induced changes in the TME of patients with MM and, more broadly, patients with cancer and establishes rational combination strategies for iberdomide with immune-enhancing therapies to treat MM.

PRMT5 inhibition shows in vitro efficacy against H3K27M-altered diffuse midline glioma, but does not extend survival in vivo.

H3K27-altered Diffuse Midline Glioma (DMG) is a universally fatal paediatric brainstem tumour. The prevalent driver mutation H3K27M creates a unique epigenetic landscape that may also establish therapeutic vulnerabilities to epigenetic inhibitors. However, while HDAC, EZH2 and BET inhibitors have proven somewhat effective in pre-clinical models, none have translated into clinical benefit due to either poor blood-brain barrier penetration, lack of efficacy or toxicity. Thus, there remains an urgent need for new DMG treatments. Here, we performed wider screening of an epigenetic inhibitor library and identified inhibitors of protein arginine methyltransferases (PRMTs) among the top hits reducing DMG cell viability. Two of the most effective inhibitors, LLY-283 and GSK591, were targeted against PRMT5 using distinct binding mechanisms and reduced the viability of a subset of DMG cells expressing wild-type TP53 and mutant ACVR1. RNA-sequencing and phenotypic analyses revealed that LLY-283 could reduce the viability, clonogenicity and invasion of DMG cells in vitro, representing three clinically important phenotypes, but failed to prolong survival in an orthotopic xenograft model. Together, these data show the challenges of DMG treatment and highlight PRMT5 inhibitors for consideration in future studies of combination treatments.

Compartmentalization proteomics revealed endolysosomal protein network changes in a goat model of atrial fibrillation.

Endolysosomes (EL) are known for their role in regulating both intracellular trafficking and proteostasis. EL facilitate the elimination of damaged membranes, protein aggregates, membranous organelles and play an important role in calcium signaling. The specific role of EL in cardiac atrial fibrillation (AF) is not well understood. We isolated atrial EL organelles from AF goat biopsies and conducted a comprehensive integrated omics analysis to study the EL-specific proteins and pathways. We also performed electron tomography, protein and enzyme assays on these biopsies. Our results revealed the upregulation of the AMPK pathway and the expression of EL-specific proteins that were not found in whole tissue lysates, including GAA, DYNLRB1, CLTB, SIRT3, CCT2, and muscle-specific HSPB2. We also observed structural anomalies, such as autophagic-vacuole formation, irregularly shaped mitochondria, and glycogen deposition. Our results provide molecular information suggesting EL play a role in AF disease process over extended time frames.

A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles-derived transcriptomic biomarkers in early-onset preeclampsia.

Background: Preeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%-8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies. Objective: The objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways. Methods/study design: We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions. Results: Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways. Conclusions: In this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.