High-Throughput Protein-Bound Amino Acid Quantification from Maize Kernels.

In cereal crops, seed quality is determined by the composition and levels of protein-bound amino acids, which account for ∼90% of the seed total amino acid content. In maize particularly, seed quality is affected by the low levels of lysine and tryptophan, two amino acids that humans and animals cannot synthesize and must obtain from the diet. The low levels of these two amino acids in seeds is due to the dominance of seed storage proteins, namely zeins, which are deficient in these two amino acids.

High-Throughput Free Amino Acid Quantification from Maize Tissues.

Amino acids in maize can exist in both a free and protein-bound state. While most amino acids are part of a protein backbone, a small percentage of them remain free and play important biological roles, serving as signaling molecules, nitrogen transporters, osmolytes, and precursors for multiple primary and secondary metabolites. Their levels vary widely especially in maize leaves, depending on the developmental stage and in response to environmental conditions.

Amino Acid Quantification from Maize Tissues.

Amino acid analysis is a vital part of analytical biochemistry. The increasing demand for low nitrogen fertilization and for plant-based diets with balanced amino acid levels and composition have made it crucial to develop reliable, fast, and affordable methods for analyzing amino acids in plants. As maize accounts for 43% of global cereal production, improving the amino acid composition of its kernels (i.

Pulmonary lysyl oxidase expression and its role in seeding Lewis lung carcinoma cells.

Copper promotes tumor growth and metastasis through a variety of mechanisms, most notably as a cofactor within the lysyl oxidase (LOX) family of secreted cuproenzymes. Members of this family, which include LOX and LOX-like enzymes LOXL1-4, catalyze the copper-dependent crosslinking of collagens and elastin within the extracellular matrix (ECM). Elevated LOX expression is associated with higher incidence and worse prognosis in multiple cancers, including colorectal, breast, pancreatic, and head and neck.

S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure.

Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences.

Resilient plants, sustainable future.

The accelerated pace of climate change over the past several years should serve as a wake-up call for all scientists, farmers, and decision makers, as it severely threatens our food supply and could result in famine, migration, war, and an overall destabilization of our society. Rapid and significant changes are therefore needed in the way we conduct research on plant resilience, develop new crop varieties, and cultivate those crops in our agricultural systems. Here, we describe the main bottlenecks for these processes and outline a set of key recommendations on how to accelerate research in this critical area for our society.

Small and Long Non-Coding RNA Analysis for Human Trophoblast-Derived Extracellular Vesicles and Their Effect on the Transcriptome Profile of Human Neural Progenitor Cells.

In mice, the fetal brain is dependent upon the placenta for factors that guide its early development. This linkage between the two organs has given rise to the term, the placenta-brain axis. A similar interrelationship between the two organs may exist in humans.

A multi-omics approach reveals a link between ribosomal protein alterations and proteome rebalancing in Arabidopsis thaliana seeds.

The ability of seeds to restore their amino acid content and composition after the elimination of the most abundant seed storage proteins (SSPs) is well-documented, yet the underlying mechanisms remain unclear. To better understand how seeds compensate for major proteomic disruptions, we conducted a comprehensive analysis on an Arabidopsis mutant lacking the three most abundant SSPs, the cruciferins. Our initial findings indicated that carbon, nitrogen, and sulfur levels, as well as total protein and oil content, remained unchanged in these mutants suggesting rebalanced seeds.

Effects of oxycodone on placental lineages: Evidence from the transcriptome profile of mouse trophoblast giant cells.

Pregnant women are often prescribed or abuse opioid drugs. The placenta is likely the key to understanding how opioids cause adverse pregnancy outcomes. Maternal oxycodone (OXY) exposure of pregnant mice leads to disturbances in the layer of invasive parietal trophoblast giant cells (pTGC) that forms the interface between the placenta and uterus.

Transcriptomic dynamics of ABA response in Brassica napus guard cells.

Drought has a significant, negative impact on crop production; and these effects are poised to increase with climate change. Plants acclimate to drought and water stress through diverse physiological responses, primarily mediated by the hormone abscisic acid (ABA). Because plants lose the majority of their water through stomatal pores on aerial surfaces of plants, stomatal closure is one of the rapid responses mediated by ABA to reduce transpirational water loss.

μREACT: A microfluidic system for rapid evaluation of trans-kingdom interactions.

Trans-kingdom interactions between cells play pivotal roles in shaping intricate ecological and biological networks. However, our grasp of these interactions remains incomplete. Specifically, the vast phylogenetic spectrum of microorganisms capable of interacting with a given host cell type remains obscure, primarily due to the absence of efficient, high-throughput, single-cell resolution systems that can rapidly decipher these interactions.

Bioinformatics and biomedical informatics with ChatGPT: Year one review.

The year 2023 marked a significant surge in the exploration of applying large language model chatbots, notably Chat Generative Pre-trained Transformer (ChatGPT), across various disciplines. We surveyed the application of ChatGPT in bioinformatics and biomedical informatics throughout the year, covering omics, genetics, biomedical text mining, drug discovery, biomedical image understanding, bioinformatics programming, and bioinformatics education. Our survey delineates the current strengths and limitations of this chatbot in bioinformatics and offers insights into potential avenues for future developments.

G2PDeep-v2: a web-based deep-learning framework for phenotype prediction and biomarker discovery using multi-omics data.

The G2PDeep-v2 server is a web-based platform powered by deep learning, for phenotype prediction and markers discovery from multi-omics data in any organisms including humans, plants, animals, and viruses. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases and other biological processes.

Arabidopsis trigalactosyldiacylglycerol1 mutants reveal a critical role for phosphtidylcholine remodeling in lipid homeostasis.

Lipid remodeling plays a critical role in plant response to abiotic stress and metabolic perturbations. Key steps in this process involve modifications of phosphatidylcholine (PC) acyl chains mediated by lysophosphatidylcholine: acyl-CoA acyltransferases (LPCATs) and phosphatidylcholine: diacylglycerol cholinephosphotransferase (ROD1). To assess their importance in lipid homeostasis, we took advantage of the trigalactosyldiacylglycerol1 (tgd1) mutant that exhibits marked increases in fatty acid synthesis and fatty acid flux through PC due to a block in inter-organelle lipid trafficking.

Rapid and Robust Polysome Isolation and Fraction RNA Extraction for Studying the Seed Translatome.

Translation of mRNA into functional proteins is a fundamental process underlying many aspects of plant growth and development. Yet, the role of translational regulation in plants across diverse tissue types, including seeds, is not well known due to the lack of methods targeting these processes. Studying the seed translatome could unveil seed-specific regulatory mechanisms, offering valuable insights for breeding efforts to enhance seed traits.

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data.

Inducible deletion of endothelial cell Efnb2 delays capillary regeneration and attenuates myofibre reinnervation following myotoxin injury in mice.

Acute injury of skeletal muscle disrupts myofibres, microvessels and motor innervation. Myofibre regeneration is well characterized, however its relationship with the regeneration of microvessels and motor nerves is undefined. Endothelial cell (EC) ephrin-B2 (Efnb2) is required for angiogenesis during embryonic development and promotes neurovascular regeneration in the adult.

Novel Zn(II)Cys Transcription Factor BcFtg1 Enhances the Virulence of the Gray Mold Fungus by Promoting Organic Acid Secretion and Carbon Source Utilization.

The Zn(II)Cys zinc cluster protein family comprises a subclass of zinc-finger proteins that serve as transcriptional regulators involved in a diverse array of fugal biological processes. However, the roles and mechanisms of the Zn(II)Cys transcription factors in mediating , a necrotrophic fungus that causes gray mold in over 1000 plant species, development and virulence remain obscure. Here, we demonstrate that a novel pathogenicity-associated factor (ungal ranscription factor containing the AL4 domain), identified from a virulence-attenuated mutant M20162 from a T-DNA insertion mutant library, plays an important role in oxalic acid (OA) secretion, carbon source absorption and cell wall integrity.

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants.

FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa.

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

Introduction: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments.

Objectives: Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies.

CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal.

In recent years, there has been a growing interest in profiling multiomic modalities within individual cells simultaneously. One such example is integrating combined single-cell RNA sequencing (scRNA-seq) data and single-cell transposase-accessible chromatin sequencing (scATAC-seq) data. Integrated analysis of diverse modalities has helped researchers make more accurate predictions and gain a more comprehensive understanding than with single-modality analysis.