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PubMed2025

scBSP: a fast and accurate tool for identifying spatially variable features from high-resolution spatial omics data.

MOTIVATION: Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in 2D and 3D space. However, the limited sequencing depth, increasing spatial resolution, and growing spatial spots in spatial omics technologies present significant computational challenges in identifying biologically meaningful molecules with variable spatial distributions across various omics modalities. RESULTS: We introduce scBSP, an open-source, versatile, and user-friendly package for identifying spatially variable features in large-scale spatial omics data. scBSP demonstrates significantly enhanced computational efficiency, processing high-resolution spatial omics data within seconds, and exhibits robust cross-platform performance by consistently identifying spatially variable features with high reproducibility across various sequencing platforms. AVAILABILITY AND IMPLEMENTATION: scBSP is available for download from R CRAN at https://cran.r-project.org/web/packages/scBSP/index.html and PyPI at https://pypi.org/project/scbsp/.

Software↗

PubMed2025

Unveiling the mechanism of micro-and-nano plastic phytotoxicity on terrestrial plants: A comprehensive review of omics approaches.

Micro-and-nano plastics (MNPs) are pervasive in terrestrial ecosystems and represent an increasing threat to plant health; however, the mechanisms underlying their phytotoxicity remain inadequately understood. MNPs can infiltrate plants through roots or leaves, causing a range of toxic effects, including inhibiting water and nutrient uptake, reducing seed germination rates, and impeding photosynthesis, resulting in oxidative damage within the plant system. The effects of MNPs are complex and influenced by various factors including size, shape, functional groups, and concentration. Recent advancements in omics technologies such as proteomics, metabolomics, transcriptomics, and microbiomics, coupled with emerging technologies like 4D omics, phenomics, spatial transcriptomics, and single-cell omics, offer unprecedented insight into the physiological, molecular, and cellular responses of terrestrial plants to MNPs exposure. This literature review synthesizes current findings regarding MNPs-induced phytotoxicity, emphasizing alterations in gene expression, protein synthesis, metabolic pathways, and physiological disruptions as revealed through omics analyses. We summarize how MNPs interact with plant cellular structures, disrupt metabolic processes, and induce oxidative stress, ultimately affecting plant growth and productivity. Furthermore, we have identified critical knowledge gaps and proposed future research directions, highlighting the necessity for integrative omics studies to elucidate the complex pathways of MNPs toxicity in terrestrial plants. In conclusion, this review underscores the potential of omics approaches to elucidate the mechanisms of MNPs-phytotoxicity and to develop strategies for mitigating the environmental impact of MNPs on plant health.

Plants↗

PubMed2026

Advancing the Deciphering of Host-Microbe Crosstalk with Spatial Omics: A Mini-Review.

Host-microbe crosstalk refers to the reciprocal influences between a host and its resident or invading microorganisms. This crosstalk plays important roles in maintaining host health, regulating physiological functions, and coordinating responses to infection. The rapid rise of spatial omics is transforming how this crosstalk is studied in both animals and plants. Unlike traditional bulk omics, which homogenize tissues and erase spatial context, spatial methods preserve in situ organization and can simultaneously capture molecular information from hosts and microbes. As a result, researchers can characterize the spatial organization of colonization and infection, identify spatial associations between microbial niches and host cell states, and visualize local host response gradients across intact tissues. Current spatial omics technologies encompass sequencing-based, imaging-based, and hybrid platforms. Spatial multi-omics approaches enable the joint measurement or integration of gene expression, protein abundance, and metabolite distributions. Although spatial association alone does not establish causality, spatial omics provides a high-resolution framework for characterizing host-microbe relationships within intact tissues and generating spatially constrained, testable hypotheses. When combined with perturbation experiments and complementary experimental evidence, these hypotheses can contribute to mechanistic interpretation of host-microbe crosstalk. Here, we review spatial omics technologies, compare their suitability and major trade-offs for host-microbe studies, and discuss computational strategies, analytical challenges, and future prospects.

Multiomics↗

PubMed2003

Metabolomics in systems biology.

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems. For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology. The aim of this review is to (a) provide an in-depth overview about metabolomic technology, (b) explore how metabolomic networks can be connected to the underlying reaction pathway structure, and (c) discuss the need to investigate integrative biochemical networks.

Models, Biological↗

PubMedDate not supplied

Application of emerging technologies in toxicology and safety assessment: regulatory perspectives.

Emerging technologies applied in the regulatory field encompass a group of technologies that are used in addition to or in replacement of the standard toxicology studies conducted to support an Investigational New Drug Application (IND) or New Drug Application (NDA). The standard package includes general toxicology studies of various duration, safety pharmacology studies, genetic toxicology studies, and reproductive toxicology studies. New and emerging technologies applied to the regulation of new drugs include the use of novel biomarkers, transfected cells and transgenic animals, and the "omics" technologies (toxicogenomics, proteomics, and metabonomics). These technologies are at various stages of regulatory development and acceptance. For example, the use of transgenic animals have gained acceptance by regulatory authorities to replace a 2-year carcinogenicity assay. Alternatively, the "omics" technologies are not sufficiently advanced to achieve regulatory acceptance as replacements, although these assays have a role early in drug development and they may prove useful as supplements to standard studies. Data from these assays have been used to address specific mechanistic questions in combination with standard toxicology assays.

Consumer Product Safety↗

PubMedDate not supplied

Biomarkers of cancer risk and therapeutic benefit: new technologies, new opportunities, and some challenges.

The biotechnology revolution offers unprecedented opportunities for identification of mechanistically-based biomarkers that report and predict cancer and other pathologies. The combination of genomic technologies with a knowledge of gene sequence and sequence conservation has made available markers that facilitate the correlation of genetic variation with biological outcomes, and "-omic" technologies allow efficient biochemical characterization of functional pathways--providing new markers of the susceptibility of individuals to cancer development, and of tumor susceptibility to specific therapies. New therapeutic agents targeted to individuals with specific genetic or biochemical characteristics already exist. The powerful -omic technologies allow efficient monitoring of gene transcripts, proteins, and intermediary metabolites, making it possible to monitor a large number of key cellular pathways simultaneously. This has enabled the identification of key biomarkers and signaling molecules associated with cell growth, cell death, and cellular metabolism. These new markers are facilitating monitoring of functional disturbance, molecular and cellular damage, and damage-response. Improved imaging technologies have made it feasible to image some of these molecular events noninvasively. To meet the challenge of evaluating and developing consensus criteria for the application of these new technologies and biomarkers, consortium approaches are being increasingly undertaken to share resources and to build a common understanding among the research, industry, and regulatory communities. These developments promise more efficient pharmaceutical product development, safer and more efficacious drugs, and provide clinical practitioners with new and better biomarkers for cancer screening, patient monitoring, and choice of therapy.

Animals↗

PubMed2026

Beyond Earth: Recent Advancements in Microgravity Biomedical and Genetic Research in Saudi Arabia.

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia's emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare.

Humans↗

PubMed2026

Reassessing Semen Analysis: Clinical Insights Beyond Sperm Count and Motility.

BACKGROUND: Semen analysis (SA), recognized by the World Health Organization (WHO) as the cornerstone of male infertility evaluation, remains indispensable in reproductive medicine. However, advances in assisted reproductive technology (ART) and artificial intelligence (AI) have highlighted the limitations of relying solely on conventional semen parameters. OBJECTIVE: To critically review the evolving clinical role of SA by integrating conventional assessment with emerging functional, molecular, and computational approaches that improve diagnostic accuracy and individualized patient care. METHODS: A narrative review of contemporary evidence was conducted, focusing on conventional semen parameters, biofunctional sperm testing, omics technologies, AI-assisted analysis, and broader clinical applications of SA. RESULTS: Conventional parameters, including sperm concentration, motility, and morphology, remain essential but inadequately reflect fertilizing capacity. Adjunctive assessments, including oxidative stress biomarkers and sperm DNA fragmentation, provide valuable insights into sperm function and reproductive potential. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, deepen mechanistic understanding, while AI enhances diagnostic precision, reproducibility, and standardization. Beyond infertility evaluation, SA also supports male contraceptive assessment, natural conception, ART, and patient counseling. CONCLUSIONS: Integrating conventional SA with functional, molecular, and AI-driven diagnostics provides a comprehensive framework for evaluating male fertility, advancing precision reproductive medicine and personalized clinical management.

cryopreservation↗

PubMed2005

Metabolomics reviewed: a new "omics" platform technology for systems biology and implications for natural products research.

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. Metabolomics (or metabonomics) has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. Metabolomics is fast becoming one of the platform sciences of the "omics", with the majority of the papers in this field having been published only in the last two years. In this review metabolomic methodologies are discussed briefly followed by a more detailed review of the use of metabolomics in integrated applications where metabolomics information has been combined with other "omic" data sets (proteomics, transcriptomics) to enable greater understanding of a biological system. The potential of metabolomics for natural product drug discovery and functional food analysis, primarily as incorporated into broader "omic" data sets, is discussed.

Biological Products↗

PubMed2004

Genetic, genomic, and bioinformatic tools for studying breast cancer progression.

Cancer susceptibility is a complex interaction of an individual's genetic composition and environmental exposures. Huge strides have been made in understanding cancer over the past 100 years, from the recognition of cancer as a genetic disease, to the identification of specific carcinogens, isolation of oncogenes and the recognition of tumor suppressors. Analysis of high-risk familial cancers has led to the discovery of new tumor suppressor genes and important cancer pathways. These families however represent only a small fraction of cancer in the general population. Most cancer instead probably results of an intricate interaction of polymorphic susceptibility genes with the sea of environmental exposures that humans experience. Although the central cadre of cancer genes is known, little is understood about the peripheral genes that likely comprise the polymorphic susceptibility loci. The challenge for cancer genetics is therefore to move forward from the Mendelian genetics of the rare familial cancer syndromes into the field of quantitative trait loci, susceptibility factors, and modifier genes. By identifying the genes that modulate an individual's susceptibility to cancer after an environmental exposure, researchers will be able to gain important insights into human biology, cancer prevention and treatment. The most efficient strategies to identify and characterize modifier loci will likely be those that are transdisciplinary, encompassing a variety of different "-omic" technologies. The application of a "trans-omic" techniques in our laboratory to the study of breast cancer dissemination is presented here as an illustration of the strategy.

Journal Article↗

PubMed2026

Emerging multidimensional biomarker system for cardiovascular-kidney-metabolic syndrome: from multi-omics integration to clinical artificial intelligence.

Cardiovascular-kidney-metabolic (CKM) syndrome is an emerging clinical entity that highlights the complex, bidirectional interplay among cardiovascular disease, chronic kidney disease, and metabolic disorders, representing a substantial and growing global health burden. This conceptualization marks a paradigm shift from viewing these conditions in isolation to understanding them as an interconnected disease continuum. Traditional biomarkers face significant limitations in the early detection, risk stratification, and precise management of CKM, necessitating a transition towards an integrated framework that captures its multisystem nature. This review systematically outlines an emerging multidimensional biomarker system encompassing key pathological axes such as metabolism, immuno-inflammation, oxidative stress, and biological aging, offering refined risk assessment beyond conventional metrics. The development of this system is propelled by revolutionary platforms, including accessible sampling techniques (e.g., dried blood spots), advanced in vitro models (e.g., multi-organ-on-a-chip), and multi-omics technologies. These platforms not only facilitate a deeper dissection of the heterogeneous origins and inter-organ crosstalk in CKM but also accelerate the discovery and validation of novel biomarkers. Concurrently, artificial intelligence serves as a pivotal tool for clinical translation, effectively integrating high-dimensional data to transform complex molecular profiles into actionable clinical insights. By enabling the construction of dynamic risk prediction and decision-support systems, this review charts a pathway toward proactive, individualized, and precise prevention and management of CKM syndrome.

Humans↗

PubMedDate not supplied

The role of mass spectrometry in plant systems biology.

Large-scale analyses of proteins and metabolites are intimately bound to advancements in MS technologies. The aim of these non-targeted "omic" technologies is to extend our understanding beyond the analysis of only parts of the system. Here, metabolomics and proteomics emerged in parallel with the development of novel mass analyzers and hyphenated techniques such as gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and multidimensional liquid chromatography coupled to mass spectrometry (LC-MS). The analysis of (i) proteins (ii) phosphoproteins, and (iii) metabolites is discussed in the context of plant physiology and environment and with a focus on novel method developments. Recently published studies measuring dynamic (quantitative) behavior at these levels are summarized; for these works, the completely sequenced plants Arabidopsis thaliana and Oryza sativa (rice) have been the primary models of choice. Particular emphasis is given to key physiological processes such as metabolism, development, stress, and defense. Moreover, attempts to combine spatial, tissue-specific resolution with systematic profiling are described. Finally, we summarize the initial steps to characterize the molecular plant phenotype as a corollary of environment and genotype.

Mass Spectrometry↗

PubMed2006

Future of toxicology--mechanisms of toxicity and drug safety: where do we go from here?

Recent high-profile drug withdrawals increase the pressure on regulators and the pharmaceutical industry to improve preclinical safety testing. Understanding mechanisms of drug toxicity is an essential step toward improving drug safety testing by providing the basis for mechanism-based risk assessments. Nonetheless, despite several decades of research on mechanisms of drug-induced toxicity and the application of various new technologies to preclinical safety assessment, the overall impact on preclinical safety testing has been modest. Assessing the risk of exposing humans to new drug candidates still depends on preclinical testing in animals, which in many, but not all cases, predicts outcomes in humans accurately. The following offers a perspective on the challenges and opportunities facing efforts to improve preclinical safety testing and outlines gaps and needs that must be addressed. A case is built for focusing solutions on defined problems within the current safety testing paradigm rather than imposing wholesale change. Targets for application of new technologies, including in silico screening, biomarkers, surrogate assays and 'omic technologies, are outlined. Improving drug safety testing will depend on improving the application of mechanism-based risk assessment but will also require improving public and private collaborations in order to focus research regarding the mechanism of drug-induced toxicity on the most important problems.

Drug Approval↗

PubMed2006

The potential of ecotoxicoproteomics in environmental monitoring: biomarker profiling in mussel plasma using ProteinChip array technology.

New global technologies, allowing simultaneous analysis of thousands of genes, proteins, and metabolites (so-called "omics" technologies), are being adopted rapidly by industry, academia, and regulatory agencies. This study evaluated the potential of proteomics in ecotoxicological research (i.e., ecotoxicoproteomics). Filter-feeding mussels (Mytilus edulis) were exposed continuously for 3 wk to oil, or oil spiked with alkylphenols and extra polycyclic aromatic hydrocarbons. The influence of chronic exposure on mussel plasma protein expression was investigated utilizing ProteinChip array technology in combination with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF MS). Results indicated that exposure to spiked oil had a more significant effect on protein expression in mussels than oil alone. In total, 83 mass peaks (intact or modified proteins/peptides) were significantly altered by spiked oil, while 49 were altered by oil. In exposed organisms, the majority of peaks were upregulated compared to controls (i.e., 69% in oil and 71% in spiked oil). Some peaks (32 in total) were affected by both treatments; however, the degree of response was higher in the spiked oil group for 25 of the 32 commonly affected features. Additionally, certain peaks revealed exposure- or gender-specific responses. Multivariate analysis with regression tree-based methods detected protein patterns associated with exposure that correctly classified masked samples with 90-95% accuracy. Similarly, 92% of females and 85% of males were correctly classified (independent of exposure). Results indicate that proteomics have the potential to make a valuable contribution to environmental monitoring and risk assessment.

Animals↗

PubMed2005

Toxicogenomics of cationic lipid-based vectors for gene therapy: impact of microarray technology.

Implementation of the high-throughput microarray gene expression profiling technology towards "toxicogenomics" has advanced identification process for safer drugs in the century of 'omics' technology. Applying such technology, in fact, to identify mechanisms for cellular toxicity can provide a means to clarify safety liabilities early in the drug discovery and developments process. The underlying principle in gene therapy is primarily targeting a specific gene (e.g., for silencing). Hence, massive efforts have been devoted to validate the gene-based therapeutics, regardless of toxicogenomics potential of delivery systems. Of the gene delivery systems, viral and non-viral vectors, as two main paradigms, have so far been widely used for delivering of the genome-based therapeutics such as oligonucleotide, small interfering RNA and DNA. However, the use of viral vectors was narrowed due to the safety concerns. Non-viral vectors were utilized as safer alternatives for gene delivery in vitro and ex-vivo; though their success for in vivo gene therapy has been limited due to low efficiency and safety issues. Fundamental principle for gene therapy is to deliver gene-based therapeutics into target cells for specific gene targeting ideally with minimal cellular toxicity. Until now, few works have been conducted about geno-compatibility of delivery systems itself, including cationic lipid-based nanosystems. Inadvertent toxicogenomic impact of gene delivery systems (e.g., cationic lipids) may intrinsically affect the outcome of gene therapy, where often only a single desired genetic change is sought. Further, there exists a possibility that gene changes induced by the lipid delivery system itself could exacerbate, attenuate or even mask the desired effects of the gene-based therapeutics. This review will focus on toxicogenomics impact of the cationic lipid-based formulations for gene therapy.

Animals↗

PubMed2003

The future of regulatory toxicology: impact of the biotechnology revolution.

The molecular biology revolution and the advent of genomic and proteomic technologies are facilitating rapid advances in our understanding of the molecular details of cell and tissue function. These advances have the potential to transform toxicological and clinical practice, and are likely to lead to the supplementation or replacement of traditional biomarkers of cellular integrity, cell and tissue homeostasis, and morphological alterations that result from cell damage or death. New technologies that permit simultaneous monitoring of many hundreds, or thousands, of macro- and small molecules ("-omics" technologies) promise to allow functional monitoring of multiple (or perhaps all) key cellular pathways simultaneously. Elucidation of cellular responses to molecular damage, including evolutionarily conserved inducible molecular defense systems, suggests the possibility of new biomarkers based on molecular responses to functional perturbations and cellular damage. Our improved understanding of the molecular basis of various pathologies suggests that monitoring specific molecular responses may provide improved prediction of human outcomes. Responses that can be monitored directly in the human should provide "bridging biomarkers" that may eliminate much of the current uncertainty in extrapolating from laboratory models to human outcome. Another aspect of genomics is our enhanced ability to associate DNA sequence variations with biological outcomes and individual sensitivity. The human genome sequence has revealed that sequence variations are very common, and may be an important determinant of variation in biological outcomes. The impending availability of a complete human haplotype map linked to standard genetic markers greatly facilitates identification of genetic variations that convey sensitivity or resistance to chemical exposures. Genetic approaches have already linked a large number of genetic variants (polymorphisms) with human diseases and adverse reactions from exposure to drugs or toxicants, suggesting an important role in sensitivity to drugs and environmental agents, disease susceptibilities, and therapeutic responses. As these opportunities are transformed into reality, regulatory toxicological practice is likely to be shaped in the future by the combination of conventional pathology, toxicology, molecular genetics, biochemistry, cell biology, and computational bio-informatics-resulting in the broad application of molecular approaches to monitoring functional disturbances.

Animals↗

PubMed2005

[Achieving pathogenesis understanding of ocular diseases by deciphering the underlying molecular pathways].

The field of ophthalmology research has experienced a revolution since the 1970's, when molecular biology techniques were gradually and widely adopted. Many of the developments generated impact that went far beyond the field of ophthalmology. A classic case was the identification and characterization of the Retinoblastoma susceptibility gene (Rb), whose impact went far beyond the rare and obscure disease, as it provides key evidence for the concept of tumor suppressor gene and the "two hit" theory of tumor formation. The identification of scores of genes involved in retinitis pigmentosum (pigmentosa), on the other hand, show cases the complexity of multi-factorial diseases. Ophthalmology researchers in China have been quick in integrating these novel tools into their research. However, the field still lags behind in the effective use of these technologies to carry out in-depth inquiries into key disease mechanisms. The advent of "omics" technologies heralded a new era in biomedical research that allows for the global and rapid survey of genetic and biochemical profiles. Effective integration of these novel technologies into ophthalmology research will have far-reaching impact for the whole field.

Biotechnology↗

PubMed2025

soFusion: facilitating tissue structure identification via spatial multi-omics data fusion.

The rapid advancement of spatial multi-omics technologies has opened new avenues for dissecting tissue architecture with unprecedented resolution. However, inherent disparities across omics modalities, such as differences in biological hierarchy and resolution, pose significant challenges for integrative analysis. To address this, we present soFusion, a method for representation learning on spatial multi-omics data that enables automated identification of tissue compartmentalization. soFusion employs a graph convolutional network (GCN) to extract latent embeddings from spatial omics profiles. To simultaneously capture both cross-modality relationships and modality-specific features, we introduce a novel strategy for intra- and inter-omics feature learning. Moreover, modality-specific decoders are designed to preserve the unique information embedded in each omics type. We evaluated soFusion on multiple datasets including gene expression, protein expression, and epigenetic features. Across all benchmarks, soFusion consistently outperformed existing methods in delineating anatomical structures and identifying spatial domains with improved continuity and reduced noise. Collectively, soFusion offers an effective solution for spatial multi-omics integration, substantially enhancing the robustness of spatial domain identification.

Humans↗