Multilayered regulation of proteome stoichiometry

Activity Regulation of a Glutamine Amidotransferase Bienzyme Complex by Substrate-Induced Subunit Interface Expansion

Glutamine amidotransferases are multienzyme machineries in which reactive ammonia is generated by a glutaminase and then transferred through a sequestered protein tunnel to a synthase active site for incorporation into diverse metabolites. To avoid wasteful metabolite consumption, there is a requirement for synchronized catalysis, but any generally applicable mechanistic insight is still lacking. As synthase activity depends on glutamine turnover, we investigated possible mechanisms controlling glutaminase catalysis using aminodeoxychorismate synthase involved in folate biosynthesis as a model. By analyzing this system in distinct states of catalysis, we found that incubation with glutamine leads to a subunit interface expansion by one-third of its original area. These changes completely enclose the glutaminase active site for sequestered catalysis and the subsequent transport of volatile ammonia to the synthase active site. In view of similar rearrangements in other glutamine amidotransferases, our observations may provide a general mechanism for the catalysis synchronization of this multienzyme family.

CoPPIs algorithm: a tool to unravel protein cooperative strategies in pathophysiological conditions

We present here the co-expressed protein-protein interactions algorithm. In addition to minimizing correlation-causality imbalance and contextualizing protein-protein interactions to the investigated systems, it combines protein-protein interactions and protein co-expression networks to identify differentially correlated functional modules. To test the algorithm, we processed a set of proteomic profiles from different brain regions of controls and subjects affected by idiopathic Parkinson's disease or carrying a GBA1 mutation. Its robustness was supported by the extraction of functional modules, related to translation and mitochondria, whose involvement in Parkinson's disease pathogenesis is well documented. Furthermore, the selection of hubs and bottlenecks from the weightedprotein-protein interactions networks provided molecular clues consistent with the Parkinson pathophysiology. Of note, like quantification, the algorithm revealed less variations when comparing disease groups than when comparing diseased and controls. However, correlation and quantification results showed low overlap, suggesting the complementarity of these measures. An observation that opens the way to a new investigation strategy that takes into account not only protein expression, but also the level of coordination among proteins that cooperate to perform a given function.

Lossless single-molecule counting to absolute quantify proteoforms

A novel immunoassay, termed Protein Interaction Coupling (PICO), is introduced to deliver clear, reference-free quantification of proteoforms - precise quantification. PICO employs a compartmentalized, homogeneous single-molecule assay with lossless and sensitive signal generation, capable of detecting down to a few molecules per reaction. Additionally, it utilizes a background-free, digital enumeration principle, known as decouplexing. PICO is presented as mathematical theories, providing a theoretical understanding of its chemistry. Consequently, PICO demonstrates precise quantification, as exemplified with recombinant and non-recombinant ErbB2 and multi-tagged peptide rTRX targets, validating quantification against internal and external references in both analytical and cellular matrices. Furthermore, PICO enables combinatorial multiplexing (cplex), a readout between any two antibodies, demonstrated by an 8-plex antibody, 12-cplex PICO, measuring functional changes of the ErbB pathway upon mock and dactolisib treatment delivering quantitative cellular stoichiometry. PICO possesses significant potential for versatile, standardized, and accurate protein measurements, offering insights into physiological and perturbed cellular processes.

Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes

Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

Perturbations in eIF3 subunit stoichiometry alter expression of ribosomal proteins and key components of the MAPK signaling pathways

Protein synthesis plays a major role in homeostasis and when dysregulated leads to various pathologies including cancer. To this end, imbalanced expression of eukaryotic translation initiation factors (eIFs) is not only a consequence but also a driver of neoplastic growth. eIF3 is the largest, multi-subunit translation initiation complex with a modular assembly, where aberrant expression of one subunit generates only partially functional subcomplexes. To comprehensively study the effects of eIF3 remodeling, we contrasted the impact of eIF3d, eIF3e or eIF3h depletion on the translatome of HeLa cells using Ribo-seq. Depletion of eIF3d or eIF3e, but not eIF3h reduced the levels of multiple components of the MAPK signaling pathways. Surprisingly, however, depletion of all three eIF3 subunits increased MAPK/ERK pathway activity. Depletion of eIF3e and partially eIF3d also increased translation of TOP mRNAs that encode mainly ribosomal proteins and other components of the translational machinery. Moreover, alterations in eIF3 subunit stoichiometry were often associated with changes in translation of mRNAs containing short uORFs, as in the case of the proto-oncogene MDM2 and the transcription factor ATF4. Collectively, perturbations in eIF3 subunit stoichiometry exert specific effect on the translatome comprising signaling and stress-related transcripts with complex 5' UTRs that are implicated in homeostatic adaptation to stress and cancer.

The two sides of chromosomal instability: drivers and brakes in cancer

Chromosomal instability (CIN) is a hallmark of cancer and is associated with tumor cell malignancy. CIN triggers a chain reaction in cells leading to chromosomal abnormalities, including deviations from the normal chromosome number or structural changes in chromosomes. CIN arises from errors in DNA replication and chromosome segregation during cell division, leading to the formation of cells with abnormal number and/or structure of chromosomes. Errors in DNA replication result from abnormal replication licensing as well as replication stress, such as double-strand breaks and stalled replication forks; meanwhile, errors in chromosome segregation stem from defects in chromosome segregation machinery, including centrosome amplification, erroneous microtubule-kinetochore attachments, spindle assembly checkpoint, or defective sister chromatids cohesion. In normal cells, CIN is deleterious and is associated with DNA damage, proteotoxic stress, metabolic alteration, cell cycle arrest, and senescence. Paradoxically, despite these negative consequences, CIN is one of the hallmarks of cancer found in over 90% of solid tumors and in blood cancers. Furthermore, CIN could endow tumors with enhanced adaptation capabilities due to increased intratumor heterogeneity, thereby facilitating adaptive resistance to therapies; however, excessive CIN could induce tumor cells death, leading to the "just-right" model for CIN in tumors. Elucidating the complex nature of CIN is crucial for understanding the dynamics of tumorigenesis and for developing effective anti-tumor treatments. This review provides an overview of causes and consequences of CIN, as well as the paradox of CIN, a phenomenon that continues to perplex researchers. Finally, this review explores the potential of CIN-based anti-tumor therapy.

A singular PpaA/AerR-like protein in Rhodospirillum rubrum rules beyond the boundaries of photosynthesis in response to the intracellular redox state

IMPORTANCE

Rhodospirillum rubrum vast metabolic versatility places it as a remarkable model bacterium and an excellent biotechnological chassis. The key component of photosynthesis (PS) studied in this work (HP1) stands out among the other members of PpaA/AerR anti-repressor family since it lacks the motif they all share: the cobalamin B-12 binding motif. Despite being reduced and poorly conserved, HP1 stills controls PS as the other members of the family, allowing a fast response to changes in the redox state of the cell. This work also shows that HP1 absence affects genes from relevant biological processes other than PS, including nitrogen fixation and stress response. From a biotechnological perspective, HP1 could be manipulated in approaches where PS is not necessary, such as hydrogen or polyhydroxyalkanoates production, to save energy.

Decoding stoichiometric protein synthesis in E. coli through translation rate parameters

E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.

Novel exported fusion enzymes with chorismate mutase and cyclohexadienyl dehydratase activity: Shikimate pathway enzymes teamed up in no man's land

Chorismate mutase (CM) and cyclohexadienyl dehydratase (CDT) catalyze two subsequent reactions in the intracellular biosynthesis of l-phenylalanine (Phe). Here, we report the discovery of novel and extremely rare bifunctional fusion enzymes, consisting of fused CM and CDT domains, which are exported from the cytoplasm. Such enzymes were found in only nine bacterial species belonging to non-pathogenic γ- or β-Proteobacteria. In γ-proteobacterial fusion enzymes, the CM domain is N-terminal to the CDT domain, whereas the order is inverted in β-Proteobacteria. The CM domains share 15% to 20% sequence identity with the AroQγ class CM holotype of Mycobacterium tuberculosis (∗MtCM), and the CDT domains 40% to 60% identity with the exported monofunctional enzyme of Pseudomonas aeruginosa (PheC). In vitro kinetics revealed a Km <7 μM, much lower than for ∗MtCM, whereas kinetic parameters are similar for CDT domains and PheC. There is no feedback inhibition of CM or CDT by the pathway's end product Phe, and no catalytic benefit of the domain fusion compared with engineered single-domain constructs. The fusion enzymes of Aequoribacter fuscus, Janthinobacterium sp. HH01, and Duganella sacchari were crystallized and their structures refined to 1.6, 1.7, and 2.4 Å resolution, respectively. Neither the crystal structures nor the size-exclusion chromatography show evidence for substrate channeling or higher oligomeric structure that could account for the cooperation of CM and CDT active sites. The genetic neighborhood with genes encoding transporter and substrate binding proteins suggests that these exported bifunctional fusion enzymes may participate in signaling systems rather than in the biosynthesis of Phe.

Single-molecule counting applied to the study of GPCR oligomerization

Single-molecule counting techniques enable a precise determination of the intracellular abundance and stoichiometry of proteins and macromolecular complexes. These details are often challenging to quantitatively assess yet are essential for our understanding of cellular function. Consider G-protein-coupled receptors-an expansive class of transmembrane signaling proteins that participate in many vital physiological functions making them a popular target for drug development. While early evidence for the role of oligomerization in receptor signaling came from ensemble biochemical and biophysical assays, innovations in single-molecule measurements are now driving a paradigm shift in our understanding of its relevance. Here, we review recent developments in single-molecule counting with a focus on photobleaching step counting and the emerging technique of quantitative single-molecule localization microscopy-with a particular emphasis on the potential for these techniques to advance our understanding of the role of oligomerization in G-protein-coupled receptor signaling.

Temporal Modulation of Differential Alternative Splicing in HaCaT Human Keratinocyte Cell Line Chronically Exposed to Arsenic for up to 28 Wk

BACKGROUND

Chronic arsenic exposure via drinking water is associated with an increased risk of developing cancer and noncancer chronic diseases. Pre-mRNAs are often subject to alternative splicing, generating mRNA isoforms encoding functionally distinct protein isoforms. The resulting imbalance in isoform species can result in pathogenic changes in critical signaling pathways. Alternative splicing as a mechanism of arsenic-induced toxicity and carcinogenicity is understudied.

OBJECTIVE

This study aimed to accurately profile differential alternative splicing events in human keratinocytes induced by chronic arsenic exposure that might play a role in carcinogenesis.

METHODS

Independent quadruplicate cultures of immortalized human keratinocytes (HaCaT) were maintained continuously for 28 wk with 0 or 100  nM sodium arsenite. RNA-sequencing (RNA-Seq) was performed with poly(A) RNA isolated from cells harvested at 7, 19, and 28 wk with subsequent replicate multivariate analysis of transcript splicing (rMATS) analysis to detect and quantify differential alternative splicing events. Reverse transcriptase-polymerase chain reaction (RT-PCR) for selected alternative splicing events was performed to validate RNA-Seq predictions. Functional enrichment was performed by gene ontology (GO) analysis of the differential alternative splicing event data set at each time point.

RESULTS

At least 600 differential alternative splicing events were detected at each time point tested, comprising all the five main types of alternative splicing and occurring in both open reading frames (ORFs) and untranslated regions (UTRs). Based on functional relevance ELK4, SHC1, and XRRA1 were selected for validation of predicted alternative splicing events at 7 wk by RT-PCR. Densitometric analysis of RT-PCR data corroborated the rMATS predicted alternative splicing for all three events. Protein expression validation of the selected alternative splicing events was challenging given that very few isoform-specific antibodies are available. GO analysis demonstrated that the enriched terms in differential alternatively spliced mRNAs changed dynamically with the time of exposure. Notably, RNA metabolism and splicing regulation pathways were enriched at the 7-wk time point, when the greatest number of differentially alternatively spliced mRNAs are detected. Our preliminary proteomic analysis demonstrated that the expression of the canonical isoforms of the splice regulators DDX42, RMB25, and SRRM2 were induced upon chronic arsenic exposure, corroborating the splicing predictions.

DISCUSSION

These results using cultures of HaCaT cells suggest that arsenic exposure disrupted an alternative splice factor network and induced time-dependent genome-wide differential alternative splicing that likely contributed to the changing proteomic landscape in arsenic-induced carcinogenesis. However, significant challenges remain in corroborating alternative splicing data at the proteomic level. https://doi.org/10.1289/EHP9676.

An expectation-maximization approach to quantifying protein stoichiometry with single-molecule imaging

Motivation

Single-molecule localization microscopy (SMLM) is a super-resolution technique capable of rendering nanometer scale images of cellular structures. Recently, much effort has gone into developing algorithms for extracting quantitative features from SMLM datasets, such as the abundance and stoichiometry of macromolecular complexes. These algorithms often require knowledge of the complicated photophysical properties of photoswitchable fluorophores.

Results

Here, we develop a calibration-free approach to quantitative SMLM built upon the observation that most photoswitchable fluorophores emit a geometrically distributed number of blinks before photobleaching. From a statistical model of a mixture of monomers, dimers and trimers, the method employs an adapted expectation-maximization algorithm to learn the protomer fractions while simultaneously determining the single-fluorophore blinking distribution. To illustrate the utility of our approach, we benchmark it on both simulated datasets and experimental datasets assembled from SMLM images of fluorescently labeled DNA nanostructures.

Availability and implementation

An implementation of our algorithm written in Python is available at: https://www.utm.utoronto.ca/milsteinlab/resources/Software/MMCode/.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.