Omics Playground: a comprehensive self-service platform for visualization, analytics and exploration of Big Omics Data

AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare

The convergence of artificial intelligence (AI) and biomedical data is transforming precision medicine by enabling the use of genetic risk factors (GRFs) for customized healthcare services based on individual needs. Although GRFs play an essential role in disease susceptibility, progression, and therapeutic outcomes, a gap exists in exploring their contribution to AI-powered precision medicine. This paper addresses this need by investigating the significance and potential of utilizing GRFs with AI in the medical field. We examine their applications, particularly emphasizing their impact on disease prediction, treatment personalization, and overall healthcare improvement. This review explores the application of AI algorithms to optimize the use of GRFs, aiming to advance precision medicine in disease screening, patient stratification, drug discovery, and understanding disease mechanisms. Through a variety of case studies and examples, we demonstrate the potential of incorporating GRFs facilitated by AI into medical practice, resulting in more precise diagnoses, targeted therapies, and improved patient outcomes. This review underscores the potential of GRFs, empowered by AI, to enhance precision medicine by improving diagnostic accuracy, treatment precision, and individualized healthcare solutions.

DLK1 Distinguishes Subsets of NF1-Associated Malignant Peripheral Nerve Sheath Tumors with Divergent Molecular Signatures

PURPOSE

Malignant peripheral nerve sheath tumor (MPNST) is the leading cause of premature death among individuals with neurofibromatosis type 1 (NF1), and the transcriptional aberrations that precede malignant transformation and contribute to MPNST tumorigenesis remain poorly defined. Alterations involving CDKN2A and components of PRC2 have been implicated as early drivers of peripheral nerve sheath tumor (PNST) evolution, but these events do not occur in all MPNST. Accordingly, emerging data have begun to highlight the importance of molecular-based stratification to improve outcomes in patients with NF1-PNST.

EXPERIMENTAL DESIGN

In this study, we perform an integrated analysis of multiple, independent datasets obtained from human patients with NF1 to gain critical insights into PNST evolution and MPNST heterogeneity.

RESULTS

We show that delta-like noncanonical Notch ligand 1 (DLK1) is significantly increased in MPNST and provide evidence that DLK1 overexpression may precede histologic changes consistent with malignancy. In complementary analyses, we find that serum levels of DLK1 are significantly higher in both mice and humans harboring MPNST compared with those without malignancy. Importantly, although DLK1 expression is increased in MPNST overall, through the integration of multiple, independent datasets, we demonstrate that divergent levels of DLK1 expression distinguish MPNST subsets characterized by unique molecular programs and potential therapeutic vulnerabilities. Specifically, we show that overexpression of DLK1 is associated with the reactivation of embryonic signatures, an immunosuppressive microenvironment, and a worse overall survival in patients with NF1-MPNST.

CONCLUSIONS

Collectively, our findings provide critical insights into MPNST tumorigenesis and support prospective studies evaluating the utility of DLK1 tissue and serum levels in augmenting diagnosis, risk assessment, and therapeutic stratification in the setting of NF1-PNST.

Revitalizing the Epigenome of Adult Jaw Periosteal Cells: Enhancing Diversity in iPSC-Derived Mesenchymal Stem Cells (iMSCs)

Induced pluripotent stem cells (iPSCs) are rapidly emerging as a transformative resource in regenerative medicine. In a previous study, our laboratory achieved a significant milestone by successfully reprograming jaw periosteal cells (JPCs) into iPSCs, which were then differentiated into iPSC-derived mesenchymal stem cells (iMSCs). Using an optimized protocol, we generated iMSCs with a remarkable osteogenic potential while exhibiting lower expression levels of the senescence markers p16 and p21 compared to the original JPCs. This study aimed to explore the epigenetic landscape by comparing the DNA methylation and transcription profiles of iMSCs with their JPC precursors, seeking to uncover key differences. Additionally, this analysis provided an opportunity for us to investigate the potential rejuvenation effects associated with cellular reprogramming. To assess the safety of the generated cells, we evaluated their ability to form teratomas through subcutaneous injection into immunodeficient mice. Our findings revealed that, while the methylation profile of iMSCs closely mirrored that of JPCs, distinct iMSC-specific methylation patterns were evident. Strikingly, the application of DNA methylation (DNAm) clocks for biological age estimation showed a dramatic reduction in DNAm age to approximately zero in iPSCs-a rejuvenation effect that persisted in the derived iMSCs. This profound reset in biological age, together with our transcriptome data, indicate that iMSCs could possess an enhanced regenerative potential compared to adult MSCs. Future in vivo studies should validate this hypothesis.

Integration of multi-omics and single-cell transcriptome reveals mitochondrial outer membrane protein-2 (MTX-2) as a prognostic biomarker and characterizes ubiquinone metabolism in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains to be one of the most prevalent and highly invasive forms of cancer. Mitochondrial outer membrane protein-2 or Metaxin-2 (MTX2), a key regulator of mitochondrial function, has been linked to cellular bioenergetics and stress response mechanisms. However, its roles in the progression and prognosis of LUAD remain largely unexplored. This study, employed a multi-omics approach, integrating transcriptomic and clinical patient data from public databases, to evaluate the expression and prognostic relevance of MTX2 in LUAD. Single-cell RNA sequencing was utilized to further explore MTX2's role in immune infiltration and interactions within the tumor microenvironment. Additionally, we validated these findings through a series of molecular biology and functional assays. Our results demonstrated that MTX2 expression was higher in LUAD tissues compared to normal lung tissues. Elevated MTX2 levels were significantly associated with poorer overall survival in LUAD patients. Functional analyses revealed that MTX2 regulates mitochondrial bioenergetics and facilitates tumor cell proliferation. Additionally, MTX2 expression was associated with increased immune cell infiltration. A pathway analysis identified cell metabolic and tumor growth pathways regulated by MTX2, supporting its role in tumor progression. Our research identifies MTX2 as a promising prognostic biomarker and therapeutic target for LUAD. Increased expression of MTX2 promotes tumor growth by altering metabolic pathways and modulating the immune response, underscoring its potential as a new target for LUAD treatment.

Polo-like kinase inhibitors increase AAV production by halting cell cycle progression

Recombinant adeno-associated viruses (rAAVs) are commonly used in gene therapy for preclinical research and therapeutic applications. Despite the clinical efficacy of rAAVs, their manufacturing involves challenges in productivity and quality, leading to limited availability. In this study, we aimed to identify compounds that increase the capacity of cells to produce AAV9 with a high-throughput small-molecule screening strategy. With the Arrayed Targeted Library for AAV Screening platform, we screened a library of 3,300 small molecules and identified several targets, including cell cycle modulators, G protein-coupled receptor modulators, histone deacetylate inhibitors, Janus kinase inhibitors, and metabolic modulators. Most notably, we identified Polo-like kinase isoform 1 (PLK1) inhibitors as enhancers of adeno-associated virus (AAV) production. Inhibiting PLK1 with HMN-214 increased AAV production, which was largely consistent across HEK293 cell lines, vector payloads, and capsid serotypes. Using cell cycle and RNA-sequencing analysis, we showed that PLK1 inhibition halts cells in the G2/M phase and blocks their exit from the M to G1 phase. These findings support that inhibiting PLK1 may enhance AAV production and could be used to develop more cost-effective methods to manufacture AAV for gene therapies.

Nicotinamide mononucleotide restores impaired metabolism, endothelial cell proliferation and angiogenesis in old sedentary male mice

Aging is accompanied by a decline in neovascularization potential and increased susceptibility to ischemic injury. Here, we confirm the age-related impaired neovascularization following ischemic leg injury and impaired angiogenesis. The age-related deficits in angiogenesis arose primarily from diminished EC proliferation capacity, but not migration or VEGF sensitivity. Aged EC harvested from the mouse skeletal muscle displayed a pro-angiogenic gene expression phenotype, along with considerable changes in metabolic genes. Metabolomics analysis and 13C glucose tracing revealed impaired ATP production and blockade in glycolysis and TCA cycle in late passage HUVECs, which occurred at nicotinamide adenine dinucleotide (NAD⁺)-dependent steps, along with NAD+ depletion. Supplementation with nicotinamide mononucleotide (NMN), a precursor of NAD⁺, enhances late-passage EC proliferation and sprouting angiogenesis from aged mice aortas. Taken together, our study illustrates the importance of NAD+-dependent metabolism in the maintenance of EC proliferation capacity with age, and the therapeutic potential of NAD precursors.

Decoding Codon Bias: The Role of tRNA Modifications in Tissue-Specific Translation

The tRNA epitranscriptome has been recognized as an important player in mRNA translation regulation. Our knowledge of the role of the tRNA epitranscriptome in fine-tuning translation via codon decoding at tissue or cell levels remains incomplete. We analyzed tRNA expression and modifications as well as codon optimality across seven mouse tissues. Our analysis revealed distinct enrichment patterns of tRNA modifications in different tissues. Queuosine (Q) tRNA modification was most enriched in the brain compared to other tissues, while mitochondrial tRNA modifications and tRNA expression were highest in the heart. Using this observation, we synthesized, and delivered in vivo, codon-mutated EGFP for Q-codons, where the C-ending Q-codons were replaced with U-ending codons. The protein levels of mutant EGFP were downregulated in liver, which is poor in Q, while in brain EGFP, levels did not change. These data show that understanding tRNA modification enrichments across tissues is not only essential for understanding codon decoding and bias but can also be utilized for optimizing gene and mRNA therapeutics to be more tissue-, cell-, or condition-specific.

Methylsulfonylmethane (MSM) Supplementation in Adult Horses Supports Improved Skeletal Muscle Inflammatory Gene Expression Following Exercise

Methylsulfonylmethane (MSM) is a sulfur-containing molecule with reported anti-inflammatory and antioxidant activities. Exercise causes the formation of free radicals and stimulates inflammatory gene expression in leukocytes and skeletal muscle. The hypothesis that dietary supplementation with MSM alters the exercise-mediated inflammatory and oxidant response was assessed in unfit adult thoroughbred geldings. Ten geldings (6.7 ± 1.6 yr) were assigned to a diet supplemented without (CON, n = 5) or with 21 g of MSM (n = 5) for 30 days. Following the supplementation period, horses performed a standardized exercise test (SET) with blood collections before (t = 0), 10 min, 1 h, 4 h, and 24 h post-SET. Skeletal muscle biopsies were retrieved from the middle gluteus before and 1 h post-SET for total RNA isolation. All horses were rested for 120 days before the experiment was repeated in a cross-over design. Plasma total antioxidant capacity was unaffected (p > 0.05) by either exercise or MSM. Plasma glutathione peroxidase activity was less (p < 0.05) in MSM horses than in the CON. Plasma IL6, IL8, IL10, and TNFα were unaffected (p > 0.05) by either exercise or diet. Transcriptomic analysis of skeletal muscle revealed 35 genes were differentially expressed (DEG; p < 0.05) by 2-fold or more in response to exercise; no MSM DEGs were noted. A comparison of the exercise by diet contrasts revealed that horses supplemented with MSM contained a greater number of exercise-responsive genes (630; logFC > 0.2; q < 0.05) by comparison to the CON (237), with many of these mapping to the immune response (71) and cytokine signal transduction (60) pathways. These results suggest supplementation of MSM as a dietary aid for improved anti-inflammatory responses in skeletal muscle following exercise.

A comparative analysis of Marburg virus-infected bat and human models from public high-throughput sequencing data

Marburg virus (MARV) disease (MVD) is an uncommon yet serious viral hemorrhagic fever that impacts humans and non-human primates. In humans, infection by the MARV is marked by rapid onset, high transmissibility, and elevated mortality rates, presenting considerable obstacles to the development of vaccines and treatments. Bats, particularly Rousettus aegyptiacus, are suspected to be natural hosts of MARV. Previous research reported asymptomatic MARV infection in bats, in stark contrast to the severe responses observed in humans and other primates. Recent MARV outbreaks highlight significant public health concerns, underscoring the need for gene expression studies during MARV progression. To investigate this, we employed two models from the Gene Expression Omnibus, including kidney cells from Rousettus aegyptiacus and primary proximal tubular cells from Homo sapiens. These models were chosen to identify changes in gene expression profiles and to examine co-regulated genes and pathways involved in MARV disease progression. Our analysis of differentially expressed genes (DEGs) revealed that these genes are mainly associated with pathways related to the complement system, innate immune response via interferons (IFNs), Wnt/β-catenin signaling, and Hedgehog signaling, which played crucial roles in MARV infection across both models. Furthermore, we also identified several potential compounds that may be useful against MARV infection. These findings offer valuable insights into the mechanisms underlying MARV's pathophysiology and suggest potential strategies for preventing transmission, managing post-infection effects, and developing future vaccines.

Transcriptomics-informed pharmacology identifies epigenetic and cell cycle regulators that enhance AAV production

Recombinant adeno-associated virus (rAAV) is a widely used viral vector for gene therapy. However, these vectors have limited availability due to manufacturing challenges with productivity and quality. These challenges can be addressed by better understanding the mechanisms that influence cellular responses during rAAV production. In this study, we aimed to identify targets that may enhance rAAV production using transcriptomic analyses of five cell lines with variable capacities for rAAV production. Using an intersectional approach, we measured the transcriptional responses of these cells during rAAV production and compared transcriptional profiles between high and base producers to identify possible targets for enhancing production. During rAAV production, we found transcriptional differences in cell cycle and nucleosome components contributed to proliferative capacity and DNA replication. We also saw upregulation of several core functions, including transcription, stress response, and Golgi and endoplasmic reticulum organization. Conversely, we saw consistent downregulation of other factors, including inhibitors of DNA-binding proteins and mitochondrial components. With a drug-connectivity analysis, we identified five classes of drugs that were predicted to enhance rAAV production. We also validated the efficacy of histone deacetylase and microtubule inhibitors. Our data uncover novel and previously identified pathways that may enhance rAAV production and quality to expand availability of rAAV for gene therapies.

From Omics to Multi-Omics: A Review of Advantages and Tradeoffs

Bioinformatics is a rapidly evolving field charged with cataloging, disseminating, and analyzing biological data. Bioinformatics started with genomics, but while genomics focuses more narrowly on the genes comprising a genome, bioinformatics now encompasses a much broader range of omics technologies. Overcoming barriers of scale and effort that plagued earlier sequencing methods, bioinformatics adopted an ambitious strategy involving high-throughput and highly automated assays. However, as the list of omics technologies continues to grow, the field of bioinformatics has changed in two fundamental ways. Despite enormous success in expanding our understanding of the biological world, the failure of bulk methods to account for biologically important variability among cells of the same or different type has led to a major shift toward single-cell and spatially resolved omics methods, which attempt to disentangle the conflicting signals contained in heterogeneous samples by examining individual cells or cell clusters. The second major shift has been the attempt to integrate two or more different classes of omics data in a single multimodal analysis to identify patterns that bridge biological layers. For example, unraveling the cause of disease may reveal a metabolite deficiency caused by the failure of an enzyme to be phosphorylated because a gene is not expressed due to aberrant methylation as a result of a rare germline variant. Conclusions: There is a fine line between superficial understanding and analysis paralysis, but like a detective novel, multi-omics increasingly provides the clues we need, if only we are able to see them.

Transcriptomic and proteomic profiling of bi-partite and tri-partite murine iPSC-derived neurospheroids under steady-state and inflammatory condition

induced-pluripotent stem cell (iPSC)-derived neurospheroid (NSPH) models are an emerging in vitro toolkit to study the influence of inflammatory triggers on neurodegeneration and repair in a 3D neural environment. In contrast to their human counterpart, the absence of murine iPSC-derived NSPHs for profound characterisation and validation studies is a major experimental research gap, even though they offer the only possibility to truly compare or validate in vitro NSPH responses with in vivo brain responses. To contribute to these developments, we here describe the generation and characterisation of 5-week-old CX3CR1eGFP+/- CCR2RFP+/- murine (m)iPSC-derived bi-partite (neurons + astrocytes) and tri-partite (neurons + astrocytes + microglia) NSPH models that can be subjected to cellular activation following pro-inflammatory stimulation. First, cytokine analysis demonstrates that both bi-partite and tri-partite NSPHs can be triggered to release IL6 and CXCL10 following three days of stimulation with, respectively, TNFα + IL1β + IFNγ and LPS + IFNγ. Additionally, immunocytochemical analysis for G3BP1 and PABPC1 revealed the development of stress granules in both bi-partite and tri-partite NSPHs after 3 days of stimulation. To further investigate the observed signs of inflammatory response and cellular stress, we performed an untargeted transcriptomic and proteomic analysis of bi- and tri-partite NSPHs under steady-state and inflammatory conditions. Here, using the combined differential gene and protein expression profiles between unstimulated and stimulated NSPHs, Ingenuity Pathway Analysis (IPA) confirms the activation of canonical pathways associated with inflammation and cellular stress in both bi-partite and tri-partite NSPHs. Moreover, our multi-omics analysis suggests a higher level of downstream inflammatory responses, impairment of homeostatic and developmental processes, as well as activation of cell death processes in stimulated tri-partite NSPHs compared to bi-partite NSPHs. Concluding, these results emphasise the advantages of including microglia in NSPH research to study inflammation-induced neurodegeneration in a 3D neural environment.

Comprehensive analysis of bulk and single-cell RNA sequencing data reveals Schlafen-5 (SLFN5) as a novel prognosis and immunity

Recent advancements have elucidated the multifaceted roles of the Schlafen (SLFN) family, including SLFN5, SLFN11, SLFN12, SLFN13, and SLFN14, which are implicated in immunological responses. However, little is known about the roles of this gene family in relation to malignancy development. The current study aimed to explore the diagnostic and prognostic potential of Schlafen family genes in colorectal adenocarcinoma (COAD) through bioinformatics analysis. Leveraging advanced bioinformatics tools of bulk RNA-sequencing and single-cell sequencing, we conducted in-depth analyses of gene expressions, functional enrichment, and survival patterns of patients with colorectal cancer compared to normal tissue. Among Schlafen family genes, the transcription levels of SLFN5 in COAD tissues were significantly elevated and correlated with poor survival outcomes. Furthermore, SLFN5 regulated the immune response via Janus kinase (JAK)/signal transduction and activator of transcription (STAT)/interferon (IFN)-alpha/beta signaling. These chemokines in inflammation are associated with diabetes and metabolism, suggesting their involvement in altered cellular energetics for COAD progress. In addition, an immune cell deconvolution analysis indicated a correlation between SLFN5 expression and immune-related cell populations, such as regulatory T cells (Tregs). These findings highlighted the potential clinical significance of SLFN5 in COAD and provided insights into its involvement in the tumor microenvironment and immune regulation. Meanwhile, the drug discovery data of SFLN5 with potential targeted small molecules suggested its therapeutic potential for COAD. Collectively, the current research demonstrated that SFLN5 play crucial roles in tumor development and serve as a prospective biomarker for COAD.

Crosstalk between Regnase-1 and -3 shapes mast cell survival and cytokine expression

Post-transcriptional regulation of immune-related transcripts by RNA-binding proteins (RBPs) impacts immune cell responses, including mast cell functionality. Despite their importance in immune regulation, the functional role of most RBPs remains to be understood. By manipulating the expression of specific RBPs in murine mast cells, coupled with mass spectrometry and transcriptomic analyses, we found that the Regnase family of proteins acts as a potent regulator of mast cell physiology. Specifically, Regnase-1 is required to maintain basic cell proliferation and survival, whereas both Regnase-1 and -3 cooperatively regulate the expression of inflammatory transcripts upon activation, with Tnf being a primary target in both human and mouse cells. Furthermore, Regnase-3 directly interacts with Regnase-1 in mast cells and is necessary to restrain Regnase-1 expression through the destabilization of its transcript. Overall, our study identifies protein interactors of endogenously expressed Regnase factors, characterizes the regulatory interplay between Regnase family members in mast cells, and establishes their role in the control of mast cell homeostasis and inflammatory responses.

Loss-of-function of activity-dependent neuroprotective protein (ADNP) by a splice-acceptor site mutation causes Helsmoortel-Van der Aa syndrome

Mutations in ADNP result in Helsmoortel-Van der Aa syndrome. Here, we describe the first de novo intronic deletion, affecting the splice-acceptor site of the first coding ADNP exon in a five-year-old girl with developmental delay and autism. Whereas exome sequencing failed to detect the non-coding deletion, genome-wide CpG methylation analysis revealed an episignature suggestive of a Helsmoortel-Van der Aa syndrome diagnosis. This diagnosis was further supported by PhenoScore, a novel facial recognition software package. Subsequent whole-genome sequencing resolved the three-base pair ADNP deletion c.[-5-1_-4del] with transcriptome sequencing showing this deletion leads to skipping of exon 4. An N-terminal truncated protein could not be detected in transfection experiments with a mutant expression vector in HEK293T cells, strongly suggesting this is a first confirmed diagnosis exclusively due to haploinsufficiency of the ADNP gene. Pathway analysis of the methylome indicated differentially methylated genes involved in brain development, the cytoskeleton, locomotion, behavior, and muscle development. Along the same line, transcriptome analysis identified most of the differentially expressed genes as upregulated, in line with the hypomethylated CpG episignature and confirmed the involvement of the cytoskeleton and muscle development pathways that are also affected in patient cell lines and animal models. In conclusion, this novel mutation for the first time demonstrates that Helsmoortel-Van der Aa syndrome can be caused by a loss-of-function mutation. Moreover, our study elegantly illustrates the use of EpiSignatures, WGS and Phenoscore as novel complementary diagnostic tools in case a of negative WES result.

Altered Extracellular Vesicle-Derived Protein and microRNA Signatures in Bronchoalveolar Lavage Fluid from Patients with Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease for which there is no cure. Accumulating research results suggest a role for extracellular vesicles (EVs) in the pathogenesis of COPD. This study aimed to uncover the involvement of EVs and their molecular cargo in the progression of COPD by identification of EV-associated protein and microRNA (miRNA) profiles. We isolated EVs from the bronchial alveolar lavage fluid (BALF) of 18 patients with COPD and 11 healthy controls using size-exclusion chromatography. EV isolates were characterized using nanoparticle tracking analysis and protein content. Proteomic analysis revealed a higher abundance of 284 proteins (log2FC > 1) and a lower abundance of 3 proteins (log2FC < -1) in EVs derived from patients with COPD. Ingenuity pathway analysis showed that proteins enriched in COPD-associated EVs trigger inflammatory responses, including neutrophil degranulation. Variances in surface receptors and ligands associated with COPD EVs suggest a preferential interaction with alveolar cells. Small RNAseq analysis identified a higher abundance of ten miRNAs and a lower abundance of one miRNA in EVs from COPD versus controls (Basemean > 100, FDR < 0.05). Our data indicate that the molecular composition of EVs in the BALF of patients with COPD is altered compared to healthy control EVs. Several components in COPD EVs were identified that may perpetuate inflammation and alveolar tissue destruction.

OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies

BACKGROUND

The results of high-throughput biology ('omic') experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features.

RESULTS

We present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access.

CONCLUSIONS

OmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator.

ADNP dysregulates methylation and mitochondrial gene expression in the cerebellum of a Helsmoortel-Van der Aa syndrome autopsy case

BACKGROUND

Helsmoortel-Van der Aa syndrome is a neurodevelopmental disorder in which patients present with autism, intellectual disability, and frequent extra-neurological features such as feeding and gastrointestinal problems, visual impairments, and cardiac abnormalities. All patients exhibit heterozygous de novo nonsense or frameshift stop mutations in the Activity-Dependent Neuroprotective Protein (ADNP) gene, accounting for a prevalence of 0.2% of all autism cases worldwide. ADNP fulfills an essential chromatin remodeling function during brain development. In this study, we investigated the cerebellum of a died 6-year-old male patient with the c.1676dupA/p.His559Glnfs*3 ADNP mutation.

RESULTS

The clinical presentation of the patient was representative of the Helsmoortel-Van der Aa syndrome. During his lifespan, he underwent two liver transplantations after which the child died because of multiple organ failure. An autopsy was performed, and various tissue samples were taken for further analysis. We performed a molecular characterization of the cerebellum, a brain region involved in motor coordination, known for its highest ADNP expression and compared it to an age-matched control subject. Importantly, epigenome-wide analysis of the ADNP cerebellum identified CpG methylation differences and expression of multiple pathways causing neurodevelopmental delay. Interestingly, transcription factor motif enrichment analysis of differentially methylated genes showed that the ADNP binding motif was the most significantly enriched. RNA sequencing of the autopsy brain further identified downregulation of the WNT signaling pathway and autophagy defects as possible causes of neurodevelopmental delay. Ultimately, label-free quantification mass spectrometry identified differentially expressed proteins involved in mitochondrial stress and sirtuin signaling pathways amongst others. Protein-protein interaction analysis further revealed a network including chromatin remodelers (ADNP, SMARCC2, HDAC2 and YY1), autophagy-related proteins (LAMP1, BECN1 and LC3) as well as a key histone deacetylating enzyme SIRT1, involved in mitochondrial energy metabolism. The protein interaction of ADNP with SIRT1 was further biochemically validated through the microtubule-end binding proteins EB1/EB3 by direct co-immunoprecipitation in mouse cerebellum, suggesting important mito-epigenetic crosstalk between chromatin remodeling and mitochondrial energy metabolism linked to autophagy stress responses. This is further supported by mitochondrial activity assays and stainings in patient-derived fibroblasts which suggest mitochondrial dysfunctions in the ADNP deficient human brain.

CONCLUSION

This study forms the baseline clinical and molecular characterization of an ADNP autopsy cerebellum, providing novel insights in the disease mechanisms of the Helsmoortel-Van der Aa syndrome. By combining multi-omic and biochemical approaches, we identified a novel SIRT1-EB1/EB3-ADNP protein complex which may contribute to autophagic flux alterations and impaired mitochondrial metabolism in the Helsmoortel-Van der Aa syndrome and holds promise as a new therapeutic target.

Transcriptomics of Marburg virus-infected primary proximal tubular cells reveals negative correlation of immune response and energy metabolism

Marburg virus, a member of the Filoviridae, is the causative agent of Marburg virus disease (MVD), a hemorrhagic fever with a case fatality rate of up to 90 %. Acute kidney injury is common in MVD and is associated with increased mortality, but its pathogenesis in MVD remains poorly understood. Interestingly, autopsies show the presence of viral proteins in different parts of the nephron, particularly in proximal tubular cells (PTC). These findings suggest a potential role for the virus in the development of MVD-related kidney injury. To shed light on this effect, we infected primary human PTC with Lake Victoria Marburg virus and conducted transcriptomic analysis at multiple time points. Unexpectedly, infection did not induce marked cytopathic effects in primary tubular cells at 20 and 40 h post infection. However, gene expression analysis revealed robust renal viral replication and dysregulation of genes essential for different cellular functions. The gene sets mainly downregulated in PTC were associated with the targets of the transcription factors MYC and E2F, DNA repair, the G2M checkpoint, as well as oxidative phosphorylation. Importantly, the downregulated factors comprise PGC-1α, a well-known factor in acute and chronic kidney injury. By contrast, the most highly upregulated gene sets were those related to the inflammatory response and cholesterol homeostasis. In conclusion, Marburg virus infects and replicates in human primary PTC and induces downregulation of processes known to be relevant for acute kidney injury as well as a strong inflammatory response.

Spatial Gene-Expression Profiling Unveils Immuno-oncogenic Programs of NF1-Associated Peripheral Nerve Sheath Tumor Progression

PURPOSE

Plexiform neurofibromas (PNF) are benign peripheral nerve sheath tumors (PNST) associated with neurofibromatosis type 1 (NF1). Despite similar histologic appearance, these neoplasms exhibit diverse evolutionary trajectories, with a subset progressing to malignant peripheral nerve sheath tumor (MPNST), the leading cause of premature death in individuals with NF1. Malignant transformation of PNF often occurs through the development of atypical neurofibroma (ANF) precursor lesions characterized by distinct histopathologic features and CDKN2A copy-number loss. Although genomic studies have uncovered key driver events promoting tumor progression, the transcriptional changes preceding malignant transformation remain poorly defined.

EXPERIMENTAL DESIGN

Here we resolve gene-expression profiles in PNST across the neurofibroma-to-MPNST continuum in NF1 patients and mouse models, revealing early molecular features associated with neurofibroma evolution and transformation.

RESULTS

Our findings demonstrate that ANF exhibit enhanced signatures of antigen presentation and immune response, which are suppressed as malignant transformation ensues. MPNST further displayed deregulated survival and mitotic fidelity pathways, and targeting key mediators of these pathways, CENPF and BIRC5, disrupted the growth and viability of human MPNST cell lines and primary murine Nf1-Cdkn2a-mutant Schwann cell precursors. Finally, neurofibromas contiguous with MPNST manifested distinct alterations in core oncogenic and immune surveillance programs, suggesting that early molecular events driving disease progression may precede histopathologic evidence of malignancy.

CONCLUSIONS

If validated prospectively in future studies, these signatures may serve as molecular diagnostic tools to augment conventional histopathologic diagnosis by identifying neurofibromas at high risk of undergoing malignant transformation, facilitating risk-adapted care.

Short-term hypercaloric carbohydrate loading increases surgical stress resilience by inducing FGF21

Dietary restriction promotes resistance to surgical stress in multiple organisms. Counterintuitively, current medical protocols recommend short-term carbohydrate-rich drinks (carbohydrate loading) prior to surgery, part of a multimodal perioperative care pathway designed to enhance surgical recovery. Despite widespread clinical use, preclinical and mechanistic studies on carbohydrate loading in surgical contexts are lacking. Here we demonstrate in ad libitum-fed mice that liquid carbohydrate loading for one week drives reductions in solid food intake, while nearly doubling total caloric intake. Similarly, in humans, simple carbohydrate intake is inversely correlated with dietary protein intake. Carbohydrate loading-induced protein dilution increases expression of hepatic fibroblast growth factor 21 (FGF21) independent of caloric intake, resulting in protection in two models of surgical stress: renal and hepatic ischemia-reperfusion injury. The protection is consistent across male, female, and aged mice. In vivo, amino acid add-back or genetic FGF21 deletion blocks carbohydrate loading-mediated protection from ischemia-reperfusion injury. Finally, carbohydrate loading induction of FGF21 is associated with the induction of the canonical integrated stress response (ATF3/4, NF-kB), and oxidative metabolism (PPARγ). Together, these data support carbohydrate loading drinks prior to surgery and reveal an essential role of protein dilution via FGF21.

CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters

Cluster analysis is one of the most widely used exploratory methods for visualization and grouping of gene expression patterns across multiple samples or treatment groups. Although several existing online tools can annotate clusters with functional terms, there is no all-in-one webserver to effectively prioritize genes/clusters using gene essentiality as well as congruency of mRNA-protein expression. Hence, we developed CAP-RNAseq that makes possible (1) upload and clustering of bulk RNA-seq data followed by identification, annotation and network visualization of all or selected clusters; and (2) prioritization using DepMap gene essentiality and/or dependency scores as well as the degree of correlation between mRNA and protein levels of genes within an expression cluster. In addition, CAP-RNAseq has an integrated primer design tool for the prioritized genes. Herein, we showed using comparisons with the existing tools and multiple case studies that CAP-RNAseq can uniquely aid in the discovery of co-expression clusters enriched with essential genes and prioritization of novel biomarker genes that exhibit high correlations between their mRNA and protein expression levels. CAP-RNAseq is applicable to RNA-seq data from different contexts including cancer and available at http://konulabapps.bilkent.edu.tr:3838/CAPRNAseq/ and the docker image is downloadable from https://hub.docker.com/r/konulab/caprnaseq.

Single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In line with these inherent aggressive characteristics, only a subset of patients shows a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel (N = 8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, our in vitro organoid analysis indicated a correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.

Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues

Single-cell gene expression analysis using sequencing (scRNA-seq) has gained increased attention in the past decades for studying cellular transcriptional programs and their heterogeneity in an unbiased manner, and novel protocols allow the simultaneous measurement of gene expression, T-cell receptor clonality and cell surface protein expression. In this article, we describe the methods to isolate scRNA/TCR-seq-compatible CD4+ T cells from murine tissues, such as skin, spleen, and lymph nodes. We describe the processing of cells and quality control parameters during library preparation, protocols for multiplexing of samples, and strategies for sequencing. Moreover, we describe a step-by-step bioinformatic analysis pipeline from sequencing data generated using these protocols. This includes quality control, preprocessing of sequencing data and demultiplexing of individual samples. We perform quantification of gene expression and extraction of T-cell receptor alpha and beta chain sequences, followed by quality control and doublet detection, and methods for harmonization and integration of datasets. Next, we describe the identification of highly variable genes and dimensionality reduction, clustering and pseudotemporal ordering of data, and we demonstrate how to visualize the results with interactive and reproducible dashboards. We will combine different analytic R-based frameworks such as Bioconductor and Seurat, illustrating how these can be interoperable to optimally analyze scRNA/TCR-seq data of CD4+ T cells from murine tissues.

Myc controls NK cell development, IL-15-driven expansion, and translational machinery

MYC is a pleiotropic transcription factor involved in cancer, cell proliferation, and metabolism. Its regulation and function in NK cells, which are innate cytotoxic lymphocytes important to control viral infections and cancer, remain poorly defined. Here, we show that mice deficient for Myc in NK cells presented a severe reduction in these lymphocytes. Myc was required for NK cell development and expansion in response to the key cytokine IL-15, which induced Myc through transcriptional and posttranslational mechanisms. Mechanistically, Myc ablation in vivo largely impacted NK cells' ribosomagenesis, reducing their translation and expansion capacities. Similar results were obtained by inhibiting MYC in human NK cells. Impairing translation by pharmacological intervention phenocopied the consequences of deleting or blocking MYC in vitro. Notably, mice lacking Myc in NK cells exhibited defective anticancer immunity, which reflected their decreased numbers of mature NK cells exerting suboptimal cytotoxic functions. These results indicate that MYC is a central node in NK cells, connecting IL-15 to translational fitness, expansion, and anticancer immunity.

The mRNA methyltransferase Mettl3 modulates cytokine mRNA stability and limits functional responses in mast cells

Mast cells are central players in allergy and asthma, and their dysregulated responses lead to reduced quality of life and life-threatening conditions such as anaphylaxis. The RNA modification N6-methyladenosine (m6A) has a prominent impact on immune cell functions, but its role in mast cells remains unexplored. Here, by optimizing tools to genetically manipulate primary mast cells, we reveal that the m6A mRNA methyltransferase complex modulates mast cell proliferation and survival. Depletion of the catalytic component Mettl3 exacerbates effector functions in response to IgE and antigen complexes, both in vitro and in vivo. Mechanistically, deletion of Mettl3 or Mettl14, another component of the methyltransferase complex, lead to the enhanced expression of inflammatory cytokines. By focusing on one of the most affected mRNAs, namely the one encoding the cytokine IL-13, we find that it is methylated in activated mast cells, and that Mettl3 affects its transcript stability in an enzymatic activity-dependent manner, requiring consensus m6A sites in the Il13 3'-untranslated region. Overall, we reveal that the m6A machinery is essential in mast cells to sustain growth and to restrain inflammatory responses.

Transcriptional Landscape of 3D vs. 2D Ovarian Cancer Cell Models

Three-dimensional (3D) cancer models are revolutionising research, allowing for the recapitulation of an in vivo-like response through the use of an in vitro system, which is more complex and physiologically relevant than traditional monolayer cultures. Cancers such as ovarian (OvCa) are prone to developing resistance, are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D cultures. However, the current models often fall short of the predicted response, where reproducibility is limited owing to the lack of standardised methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in the genetic profiles presented by a vast array of 3D cultures. An analysis of the literature (Pubmed.gov) spanning 2012-2022 was used to identify studies with paired data of 3D and 2D monolayer counterparts in addition to RNA sequencing and microarray data. From the data, 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e., agarose, collagen, or Matrigel) compared to 2D cell cultures. The top genes differentially expressed in 2D vs. 3D included C3, CXCL1, 2, and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. The top enriched gene sets for 2D vs. 3D included IFN-α and IFN-γ response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial-mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape and identify key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments.

Auranofin Synergizes with the PARP Inhibitor Olaparib to Induce ROS-Mediated Cell Death in Mutant p53 Cancers

Auranofin (AF) is a potent, off-patent thioredoxin reductase (TrxR) inhibitor that efficiently targets cancer via reactive oxygen species (ROS)- and DNA damage-mediated cell death. The goal of this study is to enhance the efficacy of AF as a cancer treatment by combining it with the poly(ADP-ribose) polymerase-1 (PARP) inhibitor olaparib (referred to as ‘aurola’). Firstly, we investigated whether mutant p53 can sensitize non-small cell lung cancer (NSCLC) and pancreatic ductal adenocarcinoma (PDAC) cancer cells to AF and olaparib treatment in p53 knock-in and knock-out models with varying p53 protein expression levels. Secondly, we determined the therapeutic range for synergistic cytotoxicity between AF and olaparib and elucidated the underlying molecular cell death mechanisms. Lastly, we evaluated the effectiveness of the combination strategy in a murine 344SQ 3D spheroid and syngeneic in vivo lung cancer model. We demonstrated that high concentrations of AF and olaparib synergistically induced cytotoxicity in NSCLC and PDAC cell lines with low levels of mutant p53 protein that were initially more resistant to AF. The aurola combination also led to the highest accumulation of ROS, which resulted in ROS-dependent cytotoxicity of mutant p53 NSCLC cells through distinct types of cell death, including caspase-3/7-dependent apoptosis, inhibited by Z-VAD-FMK, and lipid peroxidation-dependent ferroptosis, inhibited by ferrostatin-1 and alpha-tocopherol. High concentrations of both compounds were also needed to obtain a synergistic cytotoxic effect in 3D spheroids of the murine lung adenocarcinoma cell line 344SQ, which was interestingly absent in 2D. This cell line was used in a syngeneic mouse model in which the oral administration of aurola significantly delayed the growth of mutant p53 344SQ tumors in 129S2/SvPasCrl mice, while either agent alone had no effect. In addition, RNA sequencing results revealed that AF- and aurola-treated 344SQ tumors were negatively enriched for immune-related gene sets, which is in accordance with AF’s anti-inflammatory function as an anti-rheumatic drug. Only 344SQ tumors treated with aurola showed the downregulation of genes related to the cell cycle, potentially explaining the growth inhibitory effect of aurola since no apoptosis-related gene sets were enriched. Overall, this novel combination strategy of oxidative stress induction (AF) with PARP inhibition (olaparib) could be a promising treatment for mutant p53 cancers, although high concentrations of both compounds need to be reached to obtain a substantial cytotoxic effect.

Digital spatial profiling of human parathyroid tumors reveals cellular and molecular alterations linked to vitamin D deficiency

Primary hyperparathyroidism (PHPT) is a common endocrine neoplastic disorder characterized by disrupted calcium homeostasis secondary to inappropriately elevated parathyroid hormone (PTH) secretion. Low levels of serum 25-hydroxyvitamin D (25OHD) are significantly more prevalent in PHPT patients than in the general population (1-3), but the basis for this association remains unclear. We employed a spatially defined in situ whole-transcriptomics and selective proteomics profiling approach to compare gene expression patterns and cellular composition in parathyroid adenomas from vitamin D-deficient or vitamin D-replete PHPT patients. A cross-sectional panel of eucalcemic cadaveric donor parathyroid glands was examined in parallel as normal tissue controls. Here, we report that parathyroid tumors from vitamin D-deficient PHPT patients (Def-Ts) are intrinsically different from those of vitamin D-replete patients (Rep-Ts) of similar age and preoperative clinical presentation. The parathyroid oxyphil cell content is markedly higher in Def-Ts (47.8%) relative to Rep-Ts (17.8%) and normal donor glands (7.7%). Vitamin D deficiency is associated with increased expression of electron transport chain and oxidative phosphorylation pathway components. Parathyroid oxyphil cells, while morphologically distinct, are comparable to chief cells at the transcriptional level, and vitamin D deficiency affects the transcriptional profiles of both cell types in a similar manner. These data suggest that oxyphil cells are derived from chief cells and imply that their increased abundance may be induced by low vitamin D status. Gene set enrichment analysis reveals that pathways altered in Def-Ts are distinct from Rep-Ts, suggesting alternative tumor etiologies in these groups. Increased oxyphil content may thus be a morphological indicator of tumor-predisposing cellular stress.

Impact of pulmonary African trypanosomes on the immunology and function of the lung

Approximately 20% of sleeping sickness patients exhibit respiratory complications, however, with a largely unknown role of the parasite. Here we show that tsetse fly-transmitted Trypanosoma brucei parasites rapidly and permanently colonize the lungs and occupy the extravascular spaces surrounding the blood vessels of the alveoli and bronchi. They are present as nests of multiplying parasites exhibiting close interactions with collagen and active secretion of extracellular vesicles. The local immune response shows a substantial increase of monocytes, macrophages, dendritic cells and γδ and activated αβ T cells and a later influx of neutrophils. Interestingly, parasite presence results in a significant reduction of B cells, eosinophils and natural killer cells. T. brucei infected mice show no infection-associated pulmonary dysfunction, mirroring the limited pulmonary clinical complications during sleeping sickness. However, the substantial reduction of the various immune cells may render individuals more susceptible to opportunistic infections, as evident by a co-infection experiment with respiratory syncytial virus. Collectively, these observations provide insights into a largely overlooked target organ, and may trigger new diagnostic and supportive therapeutic approaches for sleeping sickness.

metaLINCS: an R package for meta-level analysis of LINCS L1000 drug signatures using stratified connectivity mapping

Summary

Accessing the collection of perturbed gene expression profiles, such as the LINCS L1000 connectivity map, is usually performed at the individual dataset level, followed by a summary performed by counting individual hits for each perturbagen. With the metaLINCS R package, we present an alternative approach that combines rank correlation and gene set enrichment analysis to identify meta-level enrichment at the perturbagen level and, in the case of drugs, at the mechanism of action level. This significantly simplifies the interpretation and highlights overarching themes in the data. We demonstrate the functionality of the package and compare its performance against those of three currently used approaches.

Availability and implementation

metaLINCS is released under GPL3 license. Source code and documentation are freely available on GitHub (https://github.com/bigomics/metaLINCS).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Interactive and Reproducible Workflows for Exploring and Modeling RNA-seq Data with pcaExplorer, Ideal, and GeneTonic

The generation and interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task. While raw data quality control, alignment, and quantification can be streamlined via efficient algorithms that can deliver the preprocessed expression matrix, a common bottleneck in the analysis of such large datasets is the subsequent in-depth, iterative processes of data exploration, statistical testing, visualization, and interpretation. Specific tools for these workflow steps are available but require a level of technical expertise which might be prohibitive for life and clinical scientists, who are left with essential pieces of information distributed among different tabular and list formats. Our protocols are centered on the joint use of our Bioconductor packages (pcaExplorer, ideal, GeneTonic) for interactive and reproducible workflows. All our packages provide an interactive and accessible experience via Shiny web applications, while still documenting the steps performed with RMarkdown as a framework to guarantee the reproducibility of the analyses, reducing the overall time to generate insights from the data at hand. These protocols guide readers through the essential steps of Exploratory Data Analysis, statistical testing, and functional enrichment analyses, followed by integration and contextualization of results. In our packages, the core elements are linked together in interactive widgets that make drill-down tasks efficient by viewing the data at a level of increased detail. Thanks to their interoperability with essential classes and gold-standard pipelines implemented in the open-source Bioconductor project and community, these protocols will permit complex tasks in RNA-seq data analysis, combining interactivity and reproducibility for following modern best scientific practices and helping to streamline the discovery process for transcriptome data. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Exploratory Data Analysis with pcaExplorer Basic Protocol 2: Differential Expression Analysis with ideal Basic Protocol 3: Interpretation of RNA-seq results with GeneTonic Support Protocol: Downloading and installing pcaExplorer, ideal, and GeneTonic Alternate Protocol: Using functions from pcaExplorer, ideal, and GeneTonic in custom analyses.

Protein Profiling of WERI-RB1 and Etoposide-Resistant WERI-ETOR Reveals New Insights into Topoisomerase Inhibitor Resistance in Retinoblastoma

Chemotherapy resistance is one of the reasons for eye loss in patients with retinoblastoma (RB). RB chemotherapy resistance has been studied in different cell culture models, such as WERI-RB1. In addition, chemotherapy-resistant RB subclones, such as the etoposide-resistant WERI-ETOR cell line have been established to improve the understanding of chemotherapy resistance in RB. The objective of this study was to characterize cell line models of an etoposide-sensitive WERI-RB1 and its etoposide-resistant subclone, WERI-ETOR, by proteomic analysis. Subsequently, quantitative proteomics data served for correlation analysis with known drug perturbation profiles. Methodically, WERI-RB1 and WERI-ETOR were cultured, and prepared for quantitative mass spectrometry (MS). This was carried out in a data-independent acquisition (DIA) mode. The raw SWATH (sequential window acquisition of all theoretical mass spectra) files were processed using neural networks in a library-free mode along with machine-learning algorithms. Pathway-enrichment analysis was performed using the REACTOME-pathway resource, and correlated to the molecular signature database (MSigDB) hallmark gene set collections for functional annotation. Furthermore, a drug-connectivity analysis using the L1000 database was carried out to associate the mechanism of action (MOA) for different anticancer reagents to WERI-RB1/WERI-ETOR signatures. A total of 4756 proteins were identified across all samples, showing a distinct clustering between the groups. Of these proteins, 64 were significantly altered (q < 0.05 & log2FC |>2|, 22 higher in WERI-ETOR). Pathway analysis revealed the “retinoid metabolism and transport” pathway as an enriched metabolic pathway in WERI-ETOR cells, while the “sphingolipid de novo biosynthesis” pathway was identified in the WERI-RB1 cell line. In addition, this study revealed similar protein signatures of topoisomerase inhibitors in WERI-ETOR cells as well as ATPase inhibitors, acetylcholine receptor antagonists, and vascular endothelial growth factor receptor (VEGFR) inhibitors in the WERI-RB1 cell line. In this study, WERI-RB1 and WERI-ETOR were analyzed as a cell line model for chemotherapy resistance in RB using data-independent MS. Analysis of the global proteome identified activation of “sphingolipid de novo biosynthesis” in WERI-RB1, and revealed future potential treatment options for etoposide resistance in RB.

Protein Expression of AEBP1, MCM4, and FABP4 Differentiate Osteogenic, Adipogenic, and Mesenchymal Stromal Stem Cells

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

The bromodomain and extra-terminal domain degrader MZ1 exhibits preclinical anti-tumoral activity in diffuse large B-cell lymphoma of the activated B cell-like type

Aim

Bromodomain and extra-terminal domain (BET) proteins are epigenetic readers that play a fundamental role in transcription regulation. Preclinical and early clinical evidence sustain BET targeting as an anti-cancer approach. BET degraders are chimeric compounds comprising of a BET inhibitor, which allows the binding to BET bromodomains, linked to a small molecule, binder for an E3 ubiquitin ligase complex, triggering BET proteins degradation via the proteasome. These degraders, called proteolysis-targeting chimeras (PROTACs), can exhibit greater target specificity compared to BET inhibitors and overcome some of their limitations, such as the upregulation of the BET proteins themselves. Here are presented data on the anti-tumor activity and the mechanism of action of the BET degrader MZ1 in diffuse large B cell lymphoma (DLBCL) of the activated B-cell like (ABC, ABC DLBCL), using a BET inhibitor as a comparison.

Methods

Established lymphoma cell lines were exposed for 72 h to increasing doses of the compounds. Cell proliferation was evaluated by using an 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazoliumbromide (MTT) assay. Fluorescent-Activated Cell Sorter (FACS) analysis was performed to measure apoptotic activation and RNA sequencing (RNA-Seq) to study the transcriptional changes induced by the compounds.

Results

MZ1, and not its negative control epimer cisMZ1, was very active with a median half maximal inhibitory concentration (IC50) of 49 nmol/L. MZ1 was more in vitro active than the BET inhibitor birabresib (OTX015). Importantly, MZ1 induced cell death in all the ABC DLBCL cell lines, while the BET inhibitor was cytotoxic only in a fraction of them. BET degrader and inhibitor shared partially similar changes at transcriptome level but the MZ1 effect was stronger and overlapped with that caused cyclin-dependent kinase 9 (CDK9) inhibition.

Conclusions

The BET degrader MZ1 had strong cytotoxic activity in all the ABC DLBCL cell lines that were tested, and, at least in vitro, it elicited more profound effects than BET inhibitors, and encourages further investigations.

GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

BACKGROUND

The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats-normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently.

RESULTS

We developed the GeneTonic software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. GeneTonic is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. GeneTonic is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility.

CONCLUSION

GeneTonic is distributed as an R package in the Bioconductor project ( https://bioconductor.org/packages/GeneTonic/ ) under the MIT license. Offering both bird's-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, GeneTonic aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.

Multi-Omics Approaches in Immunological Research

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.

BingleSeq: a user-friendly R package for bulk and single-cell RNA-Seq data analysis

BACKGROUND

RNA sequencing is an indispensable research tool used in a broad range of transcriptome analysis studies. The most common application of RNA Sequencing is differential expression analysis and it is used to determine genetic loci with distinct expression across different conditions. An emerging field called single-cell RNA sequencing is used for transcriptome profiling at the individual cell level. The standard protocols for both of these approaches include the processing of sequencing libraries and result in the generation of count matrices. An obstacle to these analyses and the acquisition of meaningful results is that they require programing expertise. Although some effort has been directed toward the development of user-friendly RNA-Seq analysis analysis tools, few have the flexibility to explore both Bulk and single-cell RNA sequencing.

IMPLEMENTATION

BingleSeq was developed as an intuitive application that provides a user-friendly solution for the analysis of count matrices produced by both Bulk and Single-cell RNA-Seq experiments. This was achieved by building an interactive dashboard-like user interface which incorporates three state-of-the-art software packages for each type of the aforementioned analyses. Furthermore, BingleSeq includes additional features such as visualization techniques, extensive functional annotation analysis and rank-based consensus for differential gene analysis results. As a result, BingleSeq puts some of the best reviewed and most widely used packages and tools for RNA-Seq analyses at the fingertips of biologists with no programing experience.

AVAILABILITY

BingleSeq is as an easy-to-install R package available on GitHub at https://github.com/dbdimitrov/BingleSeq/.

Systems Biology Approaches to Understanding the Human Immune System

Systems biology is an approach to interrogate complex biological systems through large-scale quantification of numerous biomolecules. The immune system involves >1,500 genes/proteins in many interconnected pathways and processes, and a systems-level approach is critical in broadening our understanding of the immune response to vaccination. Changes in molecular pathways can be detected using high-throughput omics datasets (e.g., transcriptomics, proteomics, and metabolomics) by using methods such as pathway enrichment, network analysis, machine learning, etc. Importantly, integration of multiple omic datasets is becoming key to revealing novel biological insights. In this perspective article, we highlight the use of protein-protein interaction (PPI) networks as a multi-omics integration approach to unravel information flow and mechanisms during complex biological events, with a focus on the immune system. This involves a combination of tools, including: InnateDB, a database of curated interactions between genes and protein products involved in the innate immunity; NetworkAnalyst, a visualization and analysis platform for InnateDB interactions; and MetaBridge, a tool to integrate metabolite data into PPI networks. The application of these systems techniques is demonstrated for a variety of biological questions, including: the developmental trajectory of neonates during the first week of life, mechanisms in host-pathogen interaction, disease prognosis, biomarker discovery, and drug discovery and repurposing. Overall, systems biology analyses of omics data have been applied to a variety of immunology-related questions, and here we demonstrate the numerous ways in which PPI network analysis can be a powerful tool in contributing to our understanding of the immune system and the study of vaccines.