Impact of C-terminal amino acid composition on protein expression in bacteria

Massive experimental quantification allows interpretable deep learning of protein aggregation

Protein aggregation is a pathological hallmark of more than 50 human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experimental datasets. Here we directly address this data shortage by experimentally quantifying the aggregation of >100,000 protein sequences. This unprecedented dataset reveals the limited performance of existing computational methods and allows us to train CANYA, a convolution-attention hybrid neural network that accurately predicts aggregation from sequence. We adapt genomic neural network interpretability analyses to reveal CANYA's decision-making process and learned grammar. Our results illustrate the power of massive experimental analysis of random sequence-spaces and provide an interpretable and robust neural network model to predict aggregation.

Screening of Plant UDP-Glycosyltransferases for Betanin Production in Yeast

To cover the rising demand for natural food dyes, new sources and production methods are needed. Microbial fermentation of nature-identical colours, such as the red pigment betanin, has the potential to be a cost-efficient alternative to plant extraction. The last step of betanin production is catalysed by a UDP-glycosyltransferase (UGT). To find a high-performing UGT, we screened 27 UGTs from different plant species and tested their ability to produce betanin in vivo in Saccharomyces cerevisiae. We identified two new UGTs likely involved in the betanin synthesis in the plant they derive from: CqGT2 (UGT73A37) from Chenopodium quinoa and BgGT2 (UGT92X1) from Bougainvillea glabra. The betanin-producing UGTs were also tested in Yarrowia lipolytica, where CqGT2 was the best-performing glycosyltransferase for betanin production. While it has previously been shown that the UGTs can glycosylate either betanidin or cyclo-DOPA to ultimately form betanin, the molecular mechanism behind the preference for the acceptor molecule has not been elucidated. Therefore, we performed in silico structural analysis to characterise the betanin-producing UGTs further, particularly by looking into their binding mechanism. The docking model suggested that a smaller binding site found in some UGTs only allows glycosylation of cDOPA, while a wider binding site allows glycosylation of both cyclo-DOPA and betanidin.

Substrate recognition and cleavage-site preferences of Lon protease

The evolutionarily conserved AAA+ Lon protease plays a pivotal role in protein homeostasis by precisely remodeling the proteome and specifically removing unfolded, damaged, and surplus natively folded regulatory proteins. Proteolysis by Lon comprises the three fundamental stages of substrate recognition via specific amino acid sequence motifs (degrons), ATP-fueled substrate unfolding and translocation into a sequestered proteolytic chamber, and cleavage of the translocated polypeptide by the peptidase domain. Although a plethora of Lon substrates have been identified in several bacterial species, broadly applicable rules that govern recognition of numerous substrates, and hence the ability to de novo identify new Lon substrates and regulatory pathways, has lagged behind. Similarly, cleavage-site preferences of Lon proteases, and whether these crucial enzymes from diverse bacterial species share similar preferences, have remained underexplored. In this study, we report the identification and characterization of a class of high-affinity autonomous C-terminal Yersinia pestis Lon recognition degrons, variants of which are present in numerous known and new Yersinia pestis-Lon substrates and broadly distributed in diverse bacterial species. Moreover, the identification of this degron group offers the predictive power to discover new Lon substrates in eubacteria. Furthermore, cleavage-site preference analyses of multiple Lon substrates reveal that the Lon peptidase domain preferentially cleaves translocated polypeptides after phenylalanine residues to generate peptides that range from 7 to 35 residues, with an average length of 11 residues, a general feature conserved among Lon proteases from phylogenetically distinct bacterial species.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

From sequence to function: Exploring biophysical properties of bacteriophage BFK20 lytic transglycosylase domain from the minor tail protein gp15

Bacteriophages have evolved different mechanisms of infection and penetration of bacterial cell walls. In Siphoviridae-like viruses, the inner tail proteins have a pivotal role in these processes and often encode lytic protein domains which increase infection efficiency. A soluble lytic transglycosylase (SLT) domain was identified in the minor tail protein gp15 from the BFK20 bacteriophage. Six fragments containing this SLT domain with adjacent regions of different lengths were cloned, expressed and purified. The biophysical properties of the two best expressing fragments were characterized by nanoDSF and CD spectroscopy, which showed that both fragments had a high refolding ability of 90 %. 3D modeling indicated that the bacteriophage BFK20 SLT domain is structurally similar to lysozyme. The degradation activity of these SLT proteins was evaluated using a lysozyme activity assay. BFK20 might use its transglycosylase activity to allow efficient phage DNA entry into the host cell by degrading bacterial peptidoglycan.

Clinically relevant mutations in regulatory regions of metabolic genes facilitate early adaptation to ciprofloxacin in Escherichia coli

The genomic landscape associated with early adaptation to ciprofloxacin is poorly understood. Although the interplay between core metabolism and antimicrobial resistance is being increasingly recognized, mutations in metabolic genes and their biological role remain elusive. Here, we exposed Escherichia coli to increasing gradients of ciprofloxacin with intermittent transfer-bottlenecking and identified mutations in three non-canonical targets linked to metabolism including a deletion (tRNA-ArgΔ414-bp) and point mutations in the regulatory regions of argI (ARG box) and narU. Our findings suggest that these mutations modulate arginine and carbohydrate metabolism, facilitate anaerobiosis and increased ATP production during ciprofloxacin stress. Furthermore, mutations in the regulatory regions of argI and narU were detected in over 70% of sequences from clinical E. coli isolates and were overrepresented among ciprofloxacin-resistant isolates. In sum, we have identified clinically relevant mutations in the regulatory regions of metabolic genes as a central theme that drives physiological changes necessary for adaptation to ciprofloxacin stress.

Exploring the neuroprotective potential of KC14 peptide from Cyprinus carpio against oxidative stress-induced neurodegeneration by regulating antioxidant mechanism

BACKGROUND

Oxidative stress, a condition characterized by excessive production of reactive oxygen species (ROS), can cause significant damage to cellular macromolecules, leading to neurodegeneration. This underscores the need for effective antioxidant therapies that can mitigate oxidative stress and its associated neurodegenerative effects. KC14 peptide derived from liver-expressed antimicrobial peptide-2 A (LEAP 2 A) from Cyprinus carpio L. has been identified as a potential therapeutic agent. This study focuses on the antioxidant and neuroprotective properties of the KC14 peptide is to evaluate its effectiveness against oxidative stress and neurodegeneration.

METHODS

The antioxidant capabilities of KC14 were initially assessed through in silico docking studies, which predicted its potential to interact with oxidative stress-related targets. Subsequently, the peptide was tested at concentrations ranging from 5 to 45 µM in both in vitro and in vivo experiments. In vivo studies involved treating H2O2-induced zebrafish larvae with KC14 peptide to analyze its effects on oxidative stress and neuroprotection.

RESULTS

KC14 peptide showed a protective effect against the developmental malformations caused by H2O2 stress, restored antioxidant enzyme activity, reduced neuronal damage, and lowered lipid peroxidation and nitric oxide levels in H2O2-induced larvae. It enhanced acetylcholinesterase activity and significantly reduced intracellular ROS levels (p < 0.05) dose-dependently. Gene expression studies showed up-regulation of antioxidant genes with KC14 treatment under H2O2 stress.

CONCLUSIONS

This study highlights the potent antioxidant activity of KC14 and its ability to confer neuroprotection against oxidative stress can provide a novel therapeutic agent for combating neurodegenerative diseases induced by oxidative stress.

Quantitative and structural changes of blood platelet cytoskeleton proteins in multiple sclerosis (MS)

Epidemiological studies show that cardiovascular events related to platelet hyperactivity remain the leading causes of death among multiple sclerosis (MS) patients. Quantitative or structural changes of platelet cytoskeleton alter their morphology and function. Here, we demonstrated, for the first time, the structural changes in MS platelets that may be related to their hyperactivity. MS platelets were found to form large aggregates compared to control platelets. In contrast to the control, the images of overactivated, irregularly shaped MS platelets show changes in the cytoskeleton architecture, fragmented microtubule rings. Furthermore, MS platelets have long and numerous pseudopodia rich in actin filaments. We showed that MS platelets and megakaryocytes, overexpress β1-tubulin and β-actin mRNAs and proteins and have altered post-translational modification patterns. Moreover, we identified two previously undisclosed mutations in the gene encoding β1-tubulin in MS. We propose that the demonstrated structural changes of platelet cytoskeleton enhance their ability to adhere, aggregate, and degranulate fueling the risk of adverse cardiovascular events in MS.

Toxin-based screening of C-terminal tags in Escherichia coli reveals the exceptional potency of ssrA-like degrons

All bacteria possess ATP-dependent proteases that destroy cytosolic proteins. These enzymes help cells mitigate proteotoxic stress, adapt to changing nutrient availability, regulate virulence phenotypes, and transition to pathogenic lifestyles. Moreover, ATP-dependent proteases have emerged as promising antibacterial and antivirulence targets in a variety of pathogens. The physiological roles of these proteases are largely defined by the complement of proteins that they degrade. Substrates are typically recognized in a highly selective manner, often via short unstructured sequences termed degrons. While a few degrons have been identified and rigorously characterized, we lack a systematic understanding of how proteases select valid degrons from the vast complexity of protein sequence space. Here, we describe a novel high-throughput screening approach in Escherichia coli that couples proteolysis of a protein toxin to cell survival. We used this method to screen a combinatorial library of C-terminal pentapeptide sequences for functionality as proteolytic degrons in wild type E. coli, and in strains lacking components of the ClpXP and ClpAP proteases. By examining the competitive enrichment of sequences over time, we found that about one percent of pentapeptide tags lead to toxin proteolysis. Interestingly, the most enriched degrons were ClpXP-dependent and highly similar to the ssrA tag, one of the most extensively characterized degrons in bacteria. Among ssrA-like sequences, we observed that specific upstream residues correlate with successful recognition. The lack of diversity among strongly enriched sequences suggests that ssrA-like tags comprise a uniquely potent class of short C-terminal degron in E. coli. Efficient proteolysis of substrates lacking such degrons likely requires adaptors or multivalent interactions. These findings broaden our understanding of the constraints that shape the bacterial proteolytic landscape. Our screening approach may be broadly applicable to probing aspects of proteolytic substrate selection in other bacterial systems.

ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach.

A Systematic Investigation of Proteoforms with N-Terminal Glycine and Their Dynamics Reveals Its Impacts on Protein Stability

The N-termini of proteins can regulate their degradation, and the same protein with different N-termini may have distinct dynamics. Recently, it was found that N-terminal glycine can serve as a degron recognized by two E3 ligases, but N-terminal glycine was also reported to stabilize proteins. Here we developed a chemoenzymatic method for selective enrichment of proteoforms with N-terminal glycine and integrated dual protease cleavage to further improve the enrichment specificity. Over 2000 unique peptides with protein N-terminal glycine were analyzed from >1000 proteins, and most of them are previously unknown, indicating the effectiveness of the current method to capture low-abundance proteoforms with N-terminal glycine. The degradation rates of proteoforms with N-terminal glycine were quantified along with those of proteins from the whole proteome. Bioinformatic analyses reveal that proteoforms with N-terminal glycine with the fastest and slowest degradation rates have different functions and localizations. Membrane proteins with N-terminal glycine and proteins with N-terminal glycine from the N-terminal methionine excision degrade more rapidly. Furthermore, the secondary structures, adjacent amino acid residues, and protease specificities for N-terminal glycine are also vital for protein degradation. The results advance our understanding of the effects of N-terminal glycine on protein properties and functions.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

Ubiquitin-independent proteasomal degradation driven by C-degron pathways

Although most eukaryotic proteins are targeted for proteasomal degradation by ubiquitination, a subset have been demonstrated to undergo ubiquitin-independent proteasomal degradation (UbInPD). However, little is known about the molecular mechanisms driving UbInPD and the degrons involved. Utilizing the GPS-peptidome approach, a systematic method for degron discovery, we found thousands of sequences that promote UbInPD; thus, UbInPD is more prevalent than currently appreciated. Furthermore, mutagenesis experiments revealed specific C-terminal degrons required for UbInPD. Stability profiling of a genome-wide collection of human open reading frames identified 69 full-length proteins subject to UbInPD. These included REC8 and CDCA4, proteins which control proliferation and survival, as well as mislocalized secretory proteins, suggesting that UbInPD performs both regulatory and protein quality control functions. In the context of full-length proteins, C termini also play a role in promoting UbInPD. Finally, we found that Ubiquilin family proteins mediate the proteasomal targeting of a subset of UbInPD substrates.

Development and Characterization of Flavin-Binding Fluorescent Proteins, Part I: Basic Characterization

Flavin-based fluorescent proteins (FbFPs) are small fluorescent proteins derived from light-oxygen-voltage (LOV) domains. The proteins bind ubiquitous endogenous flavins as chromophores and can be used as versatile in vivo reporter proteins under aerobic and anaerobic conditions. This chapter presents the methodology to identify LOV domain sequences in genomic databases; design new FbFPs; characterize their biochemical, spectroscopic, photophysical, and photochemical properties; and conduct basic fluorescence microscopy experiments.

Bacterial degrons in synthetic circuits

Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.

A versatile active learning workflow for optimization of genetic and metabolic networks

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, we describe METIS, a versatile active machine learning workflow with a simple online interface for the data-driven optimization of biological targets with minimal experiments. We demonstrate our workflow for various applications, including cell-free transcription and translation, genetic circuits, and a 27-variable synthetic CO₂-fixation cycle (CETCH cycle), improving these systems between one and two orders of magnitude. For the CETCH cycle, we explore 10²⁵ conditions with only 1,000 experiments to yield the most efficient CO₂-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system identifying unknown interactions and bottlenecks. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, aimed at democratization and standardization, the authors describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets.

Distinct responses to rare codons in select Drosophila tissues

Codon usage bias has long been appreciated to influence protein production. Yet, relatively few studies have analyzed the impacts of codon usage on tissue-specific mRNA and protein expression. Here, we use codon-modified reporters to perform an organism-wide screen in Drosophila melanogaster for distinct tissue responses to codon usage bias. These reporters reveal a cliff-like decline of protein expression near the limit of rare codon usage in endogenously expressed Drosophila genes. Near the edge of this limit, however, we find the testis and brain are uniquely capable of expressing rare codon-enriched reporters. We define a new metric of tissue-specific codon usage, the tissue-apparent Codon Adaptation Index (taCAI), to reveal a conserved enrichment for rare codon usage in the endogenously expressed genes of both Drosophila and human testis. We further demonstrate a role for rare codons in an evolutionarily young testis-specific gene, RpL10Aa. Optimizing RpL10Aa codons disrupts female fertility. Our work highlights distinct responses to rarely used codons in select tissues, revealing a critical role for codon bias in tissue biology.

Sesquiterpene Synthase Engineering and Targeted Engineering of α-Santalene Overproduction in Escherichia coli

As a natural sesquiterpene compound with numerous biological activities, α-santalene has extensive applications in the cosmetic and pharmaceutical industries. Although several α-santalene-producing microbial strains have been constructed, low productivity still hampers large-scale fermentation. Herein, we present a case of engineered sesquiterpene biosynthesis where the insufficient downstream pathway capacity limited high-level α-santalene production in Escherichia coli. The initial strain was constructed, and it produced 6.4 mg/L α-santalene. To increase α-santalene biosynthesis, we amplified the flux toward farnesyl diphosphate (FPP) precursor by screening and choosing the right FPP synthase and reprogrammed the rate-limiting downstream pathway by generating mutations in santalene synthase (Clausena lansium; ClSS). Santalene synthase was engineered by site-directed mutagenesis, resulting in the improved soluble expression of ClSS and an α-santalene titer of 887.5 mg/L; the α-santalene titer reached 1078.8 mg/L after adding a fusion tag to ClSS. The most productive pathway, which included combining precursor flux amplification and mutant synthases, conferred an approximate 169-fold increase in α-santalene levels. Maximum titers of 1272 and 2916 mg/L were achieved under shake flask and fed-batch fermentation, respectively, and were among the highest levels reported using E. coli as the host.

Extensively Drug-Resistant Klebsiella pneumoniae Counteracts Fitness and Virulence Costs That Accompanied Ceftazidime-Avibactam Resistance Acquisition

The ability of extensively drug-resistant (XDR) Klebsiella pneumoniae to rapidly acquire resistance to novel antibiotics is a global concern. Moreover, Klebsiella clonal lineages that successfully combine resistance and hypervirulence have increasingly occurred during the last years. However, the underlying mechanisms of counteracting fitness costs that accompany antibiotic resistance acquisition remain largely unexplored. Here, we investigated whether and how an XDR sequence type (ST)307 K. pneumoniae strain developed resistance against the novel drug combination ceftazidime-avibactam (CAZ-AVI) using experimental evolution. In addition, we performed in vitro and in vivo assays, molecular modeling, and bioinformatics to identify resistance-conferring processes and explore the resulting decrease in fitness and virulence. The subsequent amelioration of the initial costs was also addressed. We demonstrate that distinct mutations of the major nonselective porin OmpK36 caused CAZ-AVI resistance that persists even upon following a second experimental evolution without antibiotic selection pressure and that the Klebsiella strain compensates the resulting fitness and virulence costs. Furthermore, the genomic and transcriptomic analyses suggest the envelope stress response regulator rpoE and associated RpoE-regulated genes as drivers of this compensation. This study verifies the crucial role of OmpK36 in CAZ-AVI resistance and shows the rapid adaptation of a bacterial pathogen to compensate fitness- and virulence-associated resistance costs, which possibly contributes to the emergence of successful clonal lineages.

IMPORTANCE Extensively drug-resistant Klebsiella pneumoniae causing major outbreaks and severe infections has become a significant challenge for health care systems worldwide. Rapid resistance development against last-resort therapeutics like ceftazidime-avibactam is a significant driver for the accelerated emergence of such pathogens. Therefore, it is crucial to understand what exactly mediates rapid resistance acquisition and how bacterial pathogens counteract accompanying fitness and virulence costs. By combining bioinformatics with in vitro and in vivo phenotypic approaches, this study revealed the critical role of mutations in a particular porin channel in ceftazidime-avibactam resistance development and a major metabolic regulator for ameliorating fitness and virulence costs. These results highlight underlying mechanisms and contribute to the understanding of factors important for the emergence of successful bacterial pathogens.

DeepSec: a deep learning framework for secreted protein discovery in human body fluids

MOTIVATION

Human proteins that are secreted into different body fluids from various cells and tissues can be promising disease indicators. Modern proteomics research empowered by both qualitative and quantitative profiling techniques has made great progress in protein discovery in various human fluids. However, due to the large number of proteins and diverse modifications present in the fluids, as well as the existing technical limits of major proteomics platforms (e.g. mass spectrometry), large discrepancies are often generated from different experimental studies. As a result, a comprehensive proteomics landscape across major human fluids are not well determined.

RESULTS

To bridge this gap, we have developed a deep learning framework, named DeepSec, to identify secreted proteins in 12 types of human body fluids. DeepSec adopts an end-to-end sequence-based approach, where a Convolutional Neural Network is built to learn the abstract sequence features followed by a Bidirectional Gated Recurrent Unit with fully connected layer for protein classification. DeepSec has demonstrated promising performances with average area under the ROC curves of 0.85-0.94 on testing datasets in each type of fluids, which outperforms existing state-of-the-art methods available mostly on blood proteins. As an illustration of how to apply DeepSec in biomarker discovery research, we conducted a case study on kidney cancer by using genomics data from the cancer genome atlas and have identified 104 possible marker proteins.

AVAILABILITY

DeepSec is available at https://bmbl.bmi.osumc.edu/deepsec/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The ANXA2/S100A10 Complex—Regulation of the Oncogenic Plasminogen Receptor

The generation of the serine protease plasmin is initiated by the binding of its zymogenic precursor, plasminogen, to cell surface receptors. The proteolytic activity of plasmin, generated at the cell surface, plays a crucial role in several physiological processes, including fibrinolysis, angiogenesis, wound healing, and the invasion of cells through both the basement membrane and extracellular matrix. The seminal observation by Albert Fischer that cancer cells, but not normal cells in culture, produce large amounts of plasmin formed the basis of current-day observations that plasmin generation can be hijacked by cancer cells to allow tumor development, progression, and metastasis. Thus, the cell surface plasminogen-binding receptor proteins are critical to generating plasmin proteolytic activity at the cell surface. This review focuses on one of the twelve well-described plasminogen receptors, S100A10, which, when in complex with its regulatory partner, annexin A2 (ANXA2), forms the ANXA2/S100A10 heterotetrameric complex referred to as AIIt. We present the theme that AIIt is the quintessential cellular plasminogen receptor since it regulates the formation and the destruction of plasmin. We also introduce the term oncogenic plasminogen receptor to define those plasminogen receptors directly activated during cancer progression. We then discuss the research establishing AIIt as an oncogenic plasminogen receptor-regulated during EMT and activated by oncogenes such as SRC, RAS, HIF1α, and PML-RAR and epigenetically by DNA methylation. We further discuss the evidence derived from animal models supporting the role of S100A10 in tumor progression and oncogenesis. Lastly, we describe the potential of S100A10 as a biomarker for cancer diagnosis and prognosis.

Short tail stories: the hirudin-like factors HLF6 and HLF7 of the Asian medicinal leech, Hirudinaria manillensis

The leech-derived hirudins and hirudin-like factors (HLFs) share a common molecule structure: a short N-terminus, a central globular domain, and an elongated C-terminal tail. All parts are important for function. HLF6 and HLF7 were identified in the Asian medicinal leech, Hirudinaria manillensis. The genes of both factors encode putative splice variants that differ in length and composition of their respective C-terminal tails. In either case, the tails are considerably shorter compared to hirudins. Here we describe the functional analyses of the natural splice variants and of synthetic variants that comprise an altered N-terminus and/or a modified central globular domain. All natural splice variants of HLF6 and HLF7 display no detectable thrombin-inhibitory potency. In contrast, some synthetic variants effectively inhibit thrombin, even with tails as short as six amino acid residues in length. Our data indicate that size and composition of the C-terminal tail of hirudins and HLFs can vary in a great extent, yet the full protein may still retain the ability to inhibit thrombin.

Widespread ribosome stalling in a genome-reduced bacterium and the need for translational quality control

Trans-translation is a ubiquitous bacterial mechanism of ribosome rescue mediated by a transfer-messenger RNA (tmRNA) that adds a degradation tag to the truncated nascent polypeptide. Here, we characterize this quality control system in a genome-reduced bacterium, Mycoplasma pneumoniae (MPN), and perform a comparative analysis of protein quality control components in slow and fast-growing prokaryotes. We show in vivo that in MPN the sole quality control cytoplasmic protease (Lon) degrades efficiently tmRNA-tagged proteins. Analysis of tmRNA-mutants encoding a tag resistant to proteolysis reveals extensive tagging activity under normal growth. Unlike knockout strains, these mutants are viable demonstrating the requirement of tmRNA-mediated ribosome recycling. Chaperone and Lon steady-state levels maintain proteostasis in these mutants suggesting a model in which co-evolution of Lon and their substrates offer simple mechanisms of regulation without specialized degradation machineries. Finally, comparative analysis shows relative increase in Lon/Chaperone levels in slow-growing bacteria suggesting physiological adaptation to growth demand.

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Lon degrades efficiently tmRNA-tagged proteins in a genome-reduced bacterium

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tmRNA-tag mutants are viable and reveal extensive tagging activity in M. pneumoniae

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Co-evolution of Lon and their substrates offer simple mechanisms of regulation

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Chaperone and Lon relative levels correlate with bacterial growth rates

Effective Population Size Predicts Local Rates but Not Local Mitigation of Read-through Errors

In correctly predicting that selection efficiency is positively correlated with the effective population size (Ne), the nearly neutral theory provides a coherent understanding of between-species variation in numerous genomic parameters, including heritable error (germline mutation) rates. Does the same theory also explain variation in phenotypic error rates and in abundance of error mitigation mechanisms? Translational read-through provides a model to investigate both issues as it is common, mostly nonadaptive, and has good proxy for rate (TAA being the least leaky stop codon) and potential error mitigation via "fail-safe" 3' additional stop codons (ASCs). Prior theory of translational read-through has suggested that when population sizes are high, weak selection for local mitigation can be effective thus predicting a positive correlation between ASC enrichment and Ne. Contra to prediction, we find that ASC enrichment is not correlated with Ne. ASC enrichment, although highly phylogenetically patchy, is, however, more common both in unicellular species and in genes expressed in unicellular modes in multicellular species. By contrast, Ne does positively correlate with TAA enrichment. These results imply that local phenotypic error rates, not local mitigation rates, are consistent with a drift barrier/nearly neutral model.

Protein quality control and regulated proteolysis in the genome-reduced organism Mycoplasma pneumoniae

Protein degradation is a crucial cellular process in all-living systems. Here, using Mycoplasma pneumoniae as a model organism, we defined the minimal protein degradation machinery required to maintain proteome homeostasis. Then, we conditionally depleted the two essential ATP-dependent proteases. Whereas depletion of Lon results in increased protein aggregation and decreased heat tolerance, FtsH depletion induces cell membrane damage, suggesting a role in quality control of membrane proteins. An integrative comparative study combining shotgun proteomics and RNA-seq revealed 62 and 34 candidate substrates, respectively. Cellular localization of substrates and epistasis studies supports separate functions for Lon and FtsH. Protein half-life measurements also suggest a role for Lon-modulated protein decay. Lon plays a key role in protein quality control, degrading misfolded proteins and those not assembled into functional complexes. We propose that regulating complex assembly and degradation of isolated proteins is a mechanism that coordinates important cellular processes like cell division. Finally, by considering the entire set of proteases and chaperones, we provide a fully integrated view of how a minimal cell regulates protein folding and degradation.

Exploring the synthetic biology potential of bacteriophages for engineering non-model bacteria

Non-model bacteria like Pseudomonas putida, Lactococcus lactis and other species have unique and versatile metabolisms, offering unique opportunities for Synthetic Biology (SynBio). However, key genome editing and recombineering tools require optimization and large-scale multiplexing to unlock the full SynBio potential of these bacteria. In addition, the limited availability of a set of characterized, species-specific biological parts hampers the construction of reliable genetic circuitry. Mining of currently available, diverse bacteriophages could complete the SynBio toolbox, as they constitute an unexplored treasure trove for fully adapted metabolic modulators and orthogonally-functioning parts, driven by the longstanding co-evolution between phage and host.

FASTQINS and ANUBIS: two bioinformatic tools to explore facts and artifacts in transposon sequencing and essentiality studies

Transposon sequencing is commonly applied for identifying the minimal set of genes required for cellular life; a major challenge in fields such as evolutionary or synthetic biology. However, the scientific community has no standards at the level of processing, treatment, curation and analysis of this kind data. In addition, we lack knowledge about artifactual signals and the requirements a dataset has to satisfy to allow accurate prediction. Here, we have developed FASTQINS, a pipeline for the detection of transposon insertions, and ANUBIS, a library of functions to evaluate and correct deviating factors known and uncharacterized until now. ANUBIS implements previously defined essentiality estimate models in addition to new approaches with advantages like not requiring a training set of genes to predict general essentiality. To highlight the applicability of these tools, and provide a set of recommendations on how to analyze transposon sequencing data, we performed a comprehensive study on artifacts corrections and essentiality estimation at a 1.5-bp resolution, in the genome-reduced bacterium Mycoplasma pneumoniae. We envision FASTQINS and ANUBIS to aid in the analysis of Tn-seq procedures and lead to the development of accurate genome essentiality estimates to guide applications such as designing live vaccines or growth optimization.