Turning the Knobs: The Impact of Post-translational Modifications on Carbon Metabolism

Plants rely on the carbon fixed by photosynthesis into sugars to grow and reproduce. However, plants often face non-ideal conditions caused by biotic and abiotic stresses. These constraints impose challenges to managing sugars, the most valuable plant asset. Hence, the precise management of sugars is crucial to avoid starvation under adverse conditions and sustain growth. This review explores the role of post-translational modifications (PTMs) in the modulation of carbon metabolism. PTMs consist of chemical modifications of proteins that change protein properties, including protein-protein interaction preferences, enzymatic activity, stability, and subcellular localization. We provide a holistic view of how PTMs tune resource distribution among different physiological processes to optimize plant fitness.

Genome-wide identification and expression profiling analysis of Wnt family genes affecting adipocyte differentiation in cattle

The Wnt family features conserved glycoproteins that play roles in tissue regeneration, animal development and cell proliferation and differentiation. For its functional diversity and importance, this family has been studied in several species, but not in the Bovinae. Herein we identified 19 Wnt genes in cattle, and seven other species of Bovinae, and described their corresponding protein properties. Phylogenetic analysis clustered the 149 Wnt proteins in Bovinae, and 38 Wnt proteins from the human and mouse into 12 major clades. Wnt genes from the same subfamilies shared similar protein motif compositions and exon–intron patterns. Chromosomal distribution and collinearity analysis revealed that they were conservative in cattle and five species of Bovinae. RNA-seq data analysis indicated that Wnt genes exhibited tissue-specific expression in cattle. qPCR analysis revealed a unique expression pattern of each gene during bovine adipocytes differentiation. Finally, the comprehensive analysis indicated that Wnt2B may regulate adipose differentiation by activating FZD5, which is worthy of further study. Our study presents the first genome-wide study of the Wnt gene family in Bovinae, and lays the foundation for further functional characterization of this family in bovine adipocytes differentiation.

Monitoring protein unfolding transitions by NMR-spectroscopy

NMR-spectroscopy has certain unique advantages for recording unfolding transitions of proteins compared e.g. to optical methods. It enables per-residue monitoring and separate detection of the folded and unfolded state as well as possible equilibrium intermediates. This allows a detailed view on the state and cooperativity of folding of the protein of interest and the correct interpretation of subsequent experiments. Here we summarize in detail practical and theoretical aspects of such experiments. Certain pitfalls can be avoided, and meaningful simplification can be made during the analysis. Especially a good understanding of the NMR exchange regime and relaxation properties of the system of interest is beneficial. We show by a global analysis of signals of the folded and unfolded state of GB1 how accurate values of unfolding can be extracted and what limits different NMR detection and unfolding methods. E.g. commonly used exchangeable amides can lead to a systematic under determination of the thermodynamic protein stability. We give several perspectives of how to deal with more complex proteins and how the knowledge about protein stability at residue resolution helps to understand protein properties under crowding conditions, during phase separation and under high pressure.

Activity Cliffs As Protein-Related Phenomenon: Investigation Using Machine Learning Against Numerous Protein Kinases

Activity cliffs (ACs) are analogous compounds of significant affinity discrepancies against certain biotarget. We propose that the ACs phenomenon is protein-related and that the propensity of certain target to have ACs can be predicted by some intrinsic protein properties. We pursued this assumption by collecting the crystallographic structures of 84 protein kinases, each of which has numerous reported inhibitors (hundreds). Following data augmentation using synthetic minority oversampling technique (SMOTE), we attempted to correlate the presence/absence of ACs within the ligand pools of collected protein kinases with their corresponding protein properties using genetic algorithm (GA) coupled with variety of machine learners (MLs). Very good GA-ML models were achieved with accuracies of around 75% against external testing set. The models were further validated by Y-scrambling. Shapely additive explanations highlighted the significance of protein rotatable bonds, hydrophobic and acidic residues in relation to the presence of ACs. These results support the hypothesis that ACs are protein-related.

Towards mechanistic models of mutational effects: Deep Learning on Alzheimer's Aβ peptide

Alzheimer's Disease (AD) is a debilitating form of dementia with a high prevalence in the global population and a large burden on the community and health care systems. AD's complex pathobiology consists of extracellular β-amyloid deposition and intracellular hyperphosphorylated tau. Comprehensive mutational analyses can generate a wealth of knowledge about protein properties and enable crucial insights into molecular mechanisms of disease. Deep Mutational Scanning (DMS) has enabled multiplexed measurement of mutational effects on protein properties, including kinematics and self-organization, with unprecedented resolution. However, potential bottlenecks of DMS characterization include experimental design, data quality, and the depth of mutational coverage. Here, we apply Deep Learning to comprehensively model the mutational effect of the AD-associated peptide Aβ42 on aggregation-related biochemical traits from DMS measurements. Among tested neural network architectures, Convolutional Neural Networks (ConvNets) and Recurrent Neural Networks (RNN) are found to be the most cost-effective models with robust high performance even under insufficiently-sampled DMS studies. While sequence features are essential for satisfactory prediction from neural networks, geometric-structural features further enhance the prediction performance. Notably, we demonstrate how mechanistic insights into phenotype may be extracted from the neural networks themselves suitably designed. This methodological benefit is particularly relevant for biochemical systems displaying a strong coupling between structure and phenotype such as the conformation of Aβ42 aggregate and nucleation, as shown here using a Graph Convolutional Neural Network (GCN) developed from the protein atomic structure input. In addition to accurate imputation of missing values (which ranged up to 55% of all phenotype values at key residues), the mutationally-defined nucleation phenotype generated from a GCN shows improved resolution for identifying known disease-causing mutations relative to the original DMS phenotype. Our study suggests that neural network derived sequence-phenotype mapping can be exploited not only to provide direct support for protein engineering or genome editing but also to facilitate therapeutic design with the gained perspectives from biological modeling.

Nucleolar targeting in an early-branching eukaryote suggests a general physicochemical mechanism for ribosome protein sorting

The eukaryotic cell targets proteins to the organelles in which they function, both membrane-bound (like the nucleus) and non-membrane-bound (like the nucleolus). Nucleolar targeting relies on positively charged localisation signals, and has received rejuvenated interest since the widespread recognition of liquid-liquid phase separation (LLPS) as a mechanism contributing to nucleolus formation. Here, we exploit a new genome-wide analysis of protein localisation in an early-branching eukaryote, Trypanosoma brucei, to analyse general nucleolar protein properties. T. brucei nucleolar proteins have similar properties to those in common model eukaryotes, specifically basic amino acids. Using protein truncations and addition of candidate targeting sequences to proteins, we show both homopolymer runs and distributed basic amino acids give nucleolar partition, further aided by a nuclear localisation signal (NLS). These findings are consistent with phase separation models of nucleolar formation and protein physical properties being a major contributing mechanism for eukaryotic nucleolar targeting, conserved from the last eukaryotic common ancestor. Importantly, cytoplasmic ribosome proteins in comparison to mitochondrial ribosome proteins followed the same pattern - pointing to adaptation of physicochemical properties to assist segregation.

SARS-CoV-2 Delta Variant Displays Moderate Resistance to Neutralizing Antibodies and Spike Protein Properties of Higher Soluble ACE2 Sensitivity, Enhanced Cleavage and Fusogenic Activity

The SARS-CoV-2 B.1.617 lineage variants, Kappa (B.1.617.1) and Delta (B.1.617.2, AY) emerged during the second wave of infections in India, but the Delta variants have become dominant worldwide and continue to evolve. Here, we compared B.1.617 variants for neutralization resistance by convalescent sera, mRNA vaccine-elicited sera, and therapeutic neutralizing antibodies using a pseudovirus neutralization assay. B.1.617.1, B.1.617.2, and AY.1 pseudoviruses showed a modest 1.5- to 4.4-fold reduction in neutralization by convalescent sera and vaccine-elicited sera. In comparison, similar modest reductions were also observed for C.37, P.1, R.1, and B.1.526 pseudoviruses, but 7- and 16-fold reductions for vaccine-elicited and convalescent sera, respectively, were seen for B.1.351 pseudoviruses. Among twenty-three therapeutic antibodies tested, four antibodies showed either complete or partial loss of neutralization against B.1.617.2 pseudoviruses and six antibodies showed either complete or partial loss of neutralization against B.1.617.1 and AY.1 pseudoviruses. Our results indicate that the current mRNA-based vaccines will likely remain effective in protecting against B.1.617 variants. Finally, the P681R substitution confers efficient cleavage of B.1.617 variants’ spike proteins and the spike of Delta variants exhibited greater sensitivity to soluble ACE2 neutralization, as well as fusogenic activity, which may contribute to enhanced spread of Delta variants.

SARS-COV-2 Delta variant displays moderate resistance to neutralizing antibodies and spike protein properties of higher soluble ACE2 sensitivity, enhanced cleavage and fusogenic activity

The SARS-CoV-2 B.1.617 lineage variants, Kappa (B.1.617.1) and Delta (B.1.617.2, AY) emerged during the second wave of infections in India, but the Delta variants have become dominant worldwide and continue to evolve. The spike proteins of B.1.617.1, B.1.617.2, and AY.1 variants have several substitutions in the receptor binding domain (RBD), including L452R+E484Q, L452R+T478K, and K417N+L452R+T478K, respectively, that could potentially reduce effectiveness of therapeutic antibodies and current vaccines. Here we compared B.1.617 variants, and their single and double RBD substitutions for resistance to neutralization by convalescent sera, mRNA vaccine-elicited sera, and therapeutic neutralizing antibodies using a pseudovirus neutralization assay. Pseudoviruses with the B.1.617.1, B.1.617.2, and AY.1 spike showed a modest 1.5 to 4.4-fold reduction in neutralization titer by convalescent sera and vaccine-elicited sera. In comparison, similar modest reductions were also observed for pseudoviruses with C.37, P.1, R.1, and B.1.526 spikes, but seven- and sixteen-fold reduction for vaccine-elicited and convalescent sera, respectively, was seen for pseudoviruses with the B.1.351 spike. Four of twenty-three therapeutic neutralizing antibodies showed either complete or partial loss of neutralization against B.1.617.2 pseudoviruses due to the L452R substitution, whereas six of twenty-three therapeutic neutralizing antibodies showed either complete or partial loss of neutralization against B.1.617.1 pseudoviruses due to either the E484Q or L452R substitution. Against AY.1 pseudoviruses, the L452R and K417N substitutions accounted for the loss of neutralization by four antibodies and one antibody, respectively, whereas one antibody lost potency that could not be fully accounted for by a single RBD substitution. The modest resistance of B.1.617 variants to vaccine-elicited sera suggest that current mRNA-based vaccines will likely remain effective in protecting against B.1.617 variants, but the therapeutic antibodies need to be carefully selected based on their resistance profiles. Finally, the spike proteins of B.1.617 variants are more efficiently cleaved due to the P681R substitution, and the spike of Delta variants exhibited greater sensitivity to soluble ACE2 neutralization, as well as fusogenic activity, which may contribute to enhanced spread of Delta variants.