TDP-43 proteinopathy in ALS is triggered by loss of ASRGL1 and associated with HML-2 expression.

TAR DNA-binding protein 43 (TDP-43) proteinopathy in brain cells is the hallmark of amyotrophic lateral sclerosis (ALS) but its cause remains elusive. Asparaginase-like-1 protein (ASRGL1) cleaves isoaspartates, which alter protein folding and susceptibility to proteolysis. ASRGL1 gene harbors a copy of the human endogenous retrovirus HML-2, whose overexpression contributes to ALS pathogenesis. Here we show that ASRGL1 expression was diminished in ALS brain samples by RNA sequencing, immunohistochemistry, and western blotting. TDP-43 and ASRGL1 colocalized in neurons but, in the absence of ASRGL1, TDP-43 aggregated in the cytoplasm. TDP-43 was found to be prone to isoaspartate formation and a substrate for ASRGL1. ASRGL1 silencing triggered accumulation of misfolded, fragmented, phosphorylated and mislocalized TDP-43 in cultured neurons and motor cortex of female mice. Overexpression of ASRGL1 restored neuronal viability. Overexpression of HML-2 led to ASRGL1 silencing. Loss of ASRGL1 leading to TDP-43 aggregation may be a critical mechanism in ALS pathophysiology.

Solvent constraints for biopolymer folding and evolution in extraterrestrial environments.

We propose that spontaneous folding and molecular evolution of biopolymers are two universal aspects that must concur for life to happen. These aspects are fundamentally related to the chemical composition of biopolymers and crucially depend on the solvent in which they are embedded. We show that molecular information theory and energy landscape theory allow us to explore the limits that solvents impose on biopolymer existence. We consider 54 solvents, including water, alcohols, hydrocarbons, halogenated solvents, aromatic solvents, and low molecular weight substances made up of elements abundant in the universe, which may potentially take part in alternative biochemistries. We find that along with water, there are many solvents for which the liquid regime is compatible with biopolymer folding and evolution. We present a ranking of the solvents in terms of biopolymer compatibility. Many of these solvents have been found in molecular clouds or may be expected to occur in extrasolar planets.

Associating protein sequence positions with the modulation of quantitative phenotypes.

Although protein sequences encode the information for folding and function, understanding their link is not an easy task. Unluckily, the prediction of how specific amino acids contribute to these features is still considerably impaired. Here, we developed a simple algorithm that finds positions in a protein sequence with potential to modulate the studied quantitative phenotypes. From a few hundred protein sequences, we perform multiple sequence alignments, obtain the per-position pairwise differences for both the sequence and the observed phenotypes, and calculate the correlation between these last two quantities. We tested our methodology with four cases: archaeal Adenylate Kinases and the organisms optimal growth temperatures, microbial rhodopsins and their maximal absorption wavelengths, mammalian myoglobins and their muscular concentration, and inhibition of HIV protease clinical isolates by two different molecules. We found from 3 to 10 positions tightly associated with those phenotypes, depending on the studied case. We showed that these correlations appear using individual positions but an improvement is achieved when the most correlated positions are jointly analyzed. Noteworthy, we performed phenotype predictions using a simple linear model that links per-position divergences and differences in the observed phenotypes. Predictions are comparable to the state-of-art methodologies which, in most of the cases, are far more complex. All of the calculations are obtained at a very low information cost since the only input needed is a multiple sequence alignment of protein sequences with their associated quantitative phenotypes. The diversity of the explored systems makes our work a valuable tool to find sequence determinants of biological activity modulation and to predict various functional features for uncharacterized members of a protein family.

r/K selection of GC content in prokaryotes.

The guanine/cytosine (GC) content of prokaryotic genomes is species-specific, taking values from 16% to 77%. This diversity of selection for GC content remains contentious. We analyse the correlations between GC content and a range of phenotypic and genotypic data in thousands of prokaryotes. GC content integrates well with these traits into r/K selection theory when phenotypic plasticity is considered. High GC-content prokaryotes are r-strategists with cheaper descendants thanks to a lower average amino acid metabolic cost, colonize unstable environments thanks to flagella and a bacillus form and are generalists in terms of resource opportunism and their defence mechanisms. Low GC content prokaryotes are K-strategists specialized for stable environments that maintain homeostasis via a high-cost outer cell membrane and endospore formation as a response to nutrient deprivation, and attain a higher nutrient-to-biomass yield. The lower proteome cost of high GC content prokaryotes is driven by the association between GC-rich codons and cheaper amino acids in the genetic code, while the correlation between GC content and genome size may be partly due to functional diversity driven by r/K selection. In all, molecular diversity in the GC content of prokaryotes may be a consequence of ecological r/K selection.

Ecology theory disentangles microbial dichotomies.

Microbes are often discussed in terms of dichotomies such as copiotrophic/oligotrophic and fast/slow-growing microbes, defined using the characterisation of microbial growth in isolated cultures. The dichotomies are usually qualitative and/or study-specific, sometimes precluding clear-cut results interpretation. We can unravel microbial dichotomies as life history strategies by combining ecology theory with Monod curves, a laboratory mathematical tool of bacterial physiology that relates the specific growth rate of a microbe with the concentration of a limiting nutrient. Fitting of Monod curves provides quantities that directly correspond to key parameters in ecological theories addressing species coexistence and diversity, such as r/K selection theory, resource competition and community structure theory and the CSR triangle of life strategies. The resulting model allows us to reconcile the copiotrophic/oligotrophic and fast/slow-growing dichotomies as different subsamples of a life history strategy triangle that also includes r/K strategists. We also used the number of known carbon sources together with community structure theory to partially explain the diversity of heterotrophic microbes observed in metagenomics experiments. In sum, we propose a theoretical framework for the study of natural microbial communities that unifies several existing proposals. Its application would require the integration of metagenomics, metametabolomics, Monod curves and carbon source data.

The evolving copiotrophic/oligotrophic dichotomy: From Winogradsky to physiology and genomics.

Nearly 100 years ago, Winogradsky published a classic communication in which he described two groups of microbes, zymogenic and autochthonous. When organic matter penetrates the soil, zymogenic microbes quickly multiply and degrade it, then giving way to the slow combustion of autochthonous microbes. Although the text was originally written in French, it is often cited by English-speaking authors. We undertook a complete translation of the 1924 publication, which we provide as Supporting information. Here, we introduce the translation and describe how the zymogenic/autochthonous dichotomy shaped research questions in the study of microbial diversity and physiology. We also identify in the literature three additional and closely related dichotomies, which we propose to call exclusive copiotrophs/oligotrophs, coexisting copiotrophs/oligotrophs and fast-growing/slow-growing microbes. While Winogradsky focussed on a successional view of microbial populations over time, the current discussion is focussed on the differences in the specific growth rate of microbes as a function of the concentration of a given limiting substrate. In the future, it will be relevant to keep in mind both nutrient-focussed and time-focussed microbial dichotomies and to design experiments with both isolated laboratory cultures and multi-species communities in the spirit of Winogradsky's direct method.

Molecular Information Theory Meets Protein Folding.

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone configurational entropy, secondary structure content, residue burial layers, and mutational studies of protein stability changes. We found that the average information contained in the sequences of evolved proteins is very close to the average information needed to specify a fold ∼2.2 ± 0.3 bits/(site·operation). The effective alphabet size in evolved proteins equals the effective number of conformations of a residue in the compact unfolded state at around 5. We calculated an energy-to-information conversion efficiency upon folding of around 50%, lower than the theoretical limit of 70%, but much higher than human-built macroscopic machines. We propose a simple mapping between molecular information theory and energy landscape theory and explore the connections between sequence evolution, configurational entropy, and the energetics of protein folding.

Conformational buffering underlies functional selection in intrinsically disordered protein regions.

Many disordered proteins conserve essential functions in the face of extensive sequence variation, making it challenging to identify the mechanisms responsible for functional selection. Here we identify the molecular mechanism of functional selection for the disordered adenovirus early gene 1A (E1A) protein. E1A competes with host factors to bind the retinoblastoma (Rb) protein, subverting cell cycle regulation. We show that two binding motifs tethered by a hypervariable disordered linker drive picomolar affinity Rb binding and host factor displacement. Compensatory changes in amino acid sequence composition and sequence length lead to conservation of optimal tethering across a large family of E1A linkers. We refer to this compensatory mechanism as conformational buffering. We also detect coevolution of the motifs and linker, which can preserve or eliminate the tethering mechanism. Conformational buffering and motif-linker coevolution explain robust functional encoding within hypervariable disordered linkers and could underlie functional selection of many disordered protein regions.

Host diversification is concurrent with linear motif evolution in a Mastadenovirus hub protein.

Over one hundred Mastadenovirus types infect seven orders of mammals. Virus-host coevolution may involve cospeciation, duplication, host switch and partial extinction events. We reconstruct Mastadenovirus diversification, finding that while cospeciation is dominant, the other three events are also common in Mastadenovirus evolution. Linear motifs are fast-evolving protein functional elements and key mediators of virus-host interactions, thus likely to partake in adaptive viral evolution. We study the evolution of eleven linear motifs in the Mastadenovirus E1A protein, a hub of virus-host protein-protein interactions, in the context of host diversification. The reconstruction of linear motif gain and loss events shows fast linear motif turnover, corresponding a virus-host protein-protein interaction turnover orders of magnitude faster than in model host proteomes. Evolution of E1A linear motifs is coupled, indicating functional coordination at the protein scale, yet presents motif-specific patterns suggestive of convergent evolution. We report a pervasive association between Mastadenovirus host diversification events and the evolution of E1A linear motifs. Eight of 17 host switches associate with the gain of one linear motif and the loss of four different linear motifs, while five of nine partial extinctions associate with the loss of one linear motif. The specific changes in E1A linear motifs during a host switch or a partial extinction suggest that changes in the host molecular environment lead to modulation of the interactions with the retinoblastoma protein and host transcriptional regulators. Altogether, changes in the linear motif repertoire of a viral hub protein are associated with adaptive evolution events during Mastadenovirus evolution.

Transcription factor specificity limits the number of DNA-binding motifs.

We study the limits imposed by transcription factor specificity on the maximum number of binding motifs that can coexist in a gene regulatory network, using the SwissRegulon Fantom5 collection of 684 human transcription factor binding sites as a model. We describe transcription factor specificity using regular expressions and find that most human transcription factor binding site motifs are separated in sequence space by one to three motif-discriminating positions. We apply theorems based on the pigeonhole principle to calculate the maximum number of transcription factors that can coexist given this degree of specificity, which is in the order of ten thousand and would fully utilize the space of DNA subsequences. Taking into account an expanded DNA alphabet with modified bases can further raise this limit by several orders of magnitude, at a lower level of sequence space usage. Our results may guide the design of transcription factors at both the molecular and system scale.

NGOME-Lite: Proteome-wide prediction of spontaneous protein deamidation highlights differences between taxa.

Asparagines in proteins deamidate spontaneously, which changes the chemical structure of a protein and often affects its function. Current prediction algorithms for asparagine deamidation require a structure as an input or are too slow to be applied at a proteomic scale. We present NGOME-Lite, a new version of our sequence-based predictor for spontaneous asparagine deamidation that is faster by over two orders of magnitude at a similar degree of accuracy. The algorithm takes into account intrinsic sequence propensities and slowing down of deamidation by local structure. NGOME-Lite can run in a proteomic analysis mode that provides the half-time of the intact form of each protein, predicted by taking into account sequence propensities and structural protection or sequence propensities only, and a structure protection factor. The detailed analysis mode also provides graphical output for all Asn residues in the query sequence. We applied NGOME-Lite to over 257,000 sequences in 38 proteomes and found that different taxa differ in their predicted deamidation dynamics. Spontaneous protein deamidation is faster in Eukarya than in Bacteria because of a higher degree of structural protection in the latter. Predicted protein deamidation half-lifes correlate with protein turnover in human, mouse, rat, C. elegans and budding yeast but not in two plants and two bacteria. NGOME-Lite is implemented in a docker container available at https://ngome.proteinphysiologylab.org.

Deamidation drives molecular aging of the SARS-CoV-2 spike protein receptor-binding motif.

The spike protein is the main protein component of the SARS-CoV-2 virion surface. The spike receptor-binding motif mediates recognition of the human angiotensin-converting enzyme 2 receptor, a critical step in infection, and is the preferential target for spike-neutralizing antibodies. Posttranslational modifications of the spike receptor-binding motif have been shown to modulate viral infectivity and host immune response, but these modifications are still being explored. Here we studied asparagine deamidation of the spike protein, a spontaneous event that leads to the appearance of aspartic and isoaspartic residues, which affect both the protein backbone and its charge. We used computational prediction and biochemical experiments to identify five deamidation hotspots in the SARS-CoV-2 spike protein. Asparagine residues 481 and 501 in the receptor-binding motif deamidate with a half-life of 16.5 and 123 days at 37 °C, respectively. Deamidation is significantly slowed at 4 °C, indicating a strong dependence of spike protein molecular aging on environmental conditions. Deamidation of the spike receptor-binding motif decreases the equilibrium constant for binding to the human angiotensin-converting enzyme 2 receptor more than 3.5-fold, yet its high conservation pattern suggests some positive effect on viral fitness. We propose a model for deamidation of the full SARS-CoV-2 virion illustrating how deamidation of the spike receptor-binding motif could lead to the accumulation on the virion surface of a nonnegligible chemically diverse spike population in a timescale of days. Our findings provide a potential mechanism for molecular aging of the spike protein with significant consequences for understanding virus infectivity and vaccine development.

A Thermodynamic Analysis of the Binding Specificity between Four Human PDZ Domains and Eight Host, Viral and Designed Ligands.

PDZ domains are binding modules mostly involved in cell signaling and cell-cell junctions. These domains are able to recognize a wide variety of natural targets and, among the PDZ partners, viruses have been discovered to interact with their host via a PDZ domain. With such an array of relevant and diverse interactions, PDZ binding specificity has been thoroughly studied and a traditional classification has grouped PDZ domains in three major specificity classes. In this work, we have selected four human PDZ domains covering the three canonical specificity-class binding mode and a set of their corresponding binders, including host/natural, viral and designed PDZ motifs. Through calorimetric techniques, we have covered the entire cross interactions between the selected PDZ domains and partners. The results indicate a rather basic specificity in each PDZ domain, with two of the domains that bind their cognate and some non-cognate ligands and the two other domains that basically bind their cognate partners. On the other hand, the host partners mostly bind their corresponding PDZ domain and, interestingly, the viral ligands are able to bind most of the studied PDZ domains, even those not previously described. Some viruses may have evolved to use of the ability of the PDZ fold to bind multiple targets, with resulting affinities for the virus-host interactions that are, in some cases, higher than for host-host interactions.

Thousands of protein linear motif classes may still be undiscovered.

Linear motifs are short protein subsequences that mediate protein interactions. Hundreds of motif classes including thousands of motif instances are known. Our theory estimates how many motif classes remain undiscovered. As commonly done, we describe motif classes as regular expressions specifying motif length and the allowed amino acids at each motif position. We measure motif specificity for a pair of motif classes by quantifying how many motif-discriminating positions prevent a protein subsequence from matching the two classes at once. We derive theorems for the maximal number of motif classes that can simultaneously maintain a certain number of motif-discriminating positions between all pairs of classes in the motif universe, for a given amino acid alphabet. We also calculate the fraction of all protein subsequences that would belong to a motif class if all potential motif classes came into existence. Naturally occurring pairs of motif classes present most often a single motif-discriminating position. This mild specificity maximizes the potential number of coexisting motif classes, the expansion of the motif universe due to amino acid modifications and the fraction of amino acid sequences that code for a motif instance. As a result, thousands of linear motif classes may remain undiscovered.

Developing synthetic biology in Argentina: the Latin American TECNOx community as an alternative way for growth of the field.

Synthetic biology emerged in the USA and Europe twenty years ago and quickly developed innovative research and technology as a result of continued funding. Synthetic biology is also growing in many developing countries of Africa, Asia and Latin America, where it could have a large economic impact by helping its use of genetic biodiversity in order to boost existing industries. Starting in 2011, Argentine synthetic biology developed along an idiosyncratic path. In 2011-2012, the main focus was not exclusively research but also on community building through teaching and participation in iGEM, following the template of the early "MIT school" of synthetic biology. In 2013-2015, activities diversified and included society-centered projects, social science studies on synthetic biology and bioart. Standard research outputs such as articles and industrial applications helped consolidate several academic working groups. Since 2016, the lack of a critical mass of researchers and a funding crisis were partially compensated by establishing links with Latin American synthetic biologists and with other socially oriented open technology collectives. The TECNOx community is a central node in this growing research and technology network. The first four annual TECNOx meetings brought together synthetic biologists with other open science and engineering platforms and explored the relationship of Latin American technologies with entrepreneurship, open hardware, ethics and human rights. In sum, the socioeconomic context encouraged Latin American synthetic biology to develop in a meandering and diversifying manner. This revealed alternative ways for growth of the field that may be relevant to other developing countries.

Topology Dictates Evolution of Regulatory Cysteines in a Family of Viral Oncoproteins.

Redox regulation in biology is largely operated by cysteine chemistry in response to a variety of cell environmental and intracellular stimuli. The high chemical reactivity of cysteines determines their conservation in functional roles, but their presence can also result in harmful oxidation limiting their general use by proteins. Papillomaviruses constitute a unique system for studying protein sequence evolution since there are hundreds of anciently evolved stable genomes. E7, the viral transforming factor, is a dimeric, cysteine-rich oncoprotein that shows both conserved structural and variable regulatory cysteines constituting an excellent model for uncovering the mechanism that drives the acquisition of redox-sensitive groups. By analyzing over 300 E7 sequences, we found that although noncanonical cysteines show no obvious sequence conservation pattern, they are nonrandomly distributed based on topological constrains. Regulatory residues are strictly excluded from six positions stabilizing the hydrophobic core while they are enriched in key positions located at the dimerization interface or around the Zn+2 ion. Oxidation of regulatory cysteines is linked to dimer dissociation, acting as a reversible redox-sensing mechanism that triggers a conformational switch. Based on comparative sequence analysis, molecular dynamics simulations and biophysical analysis, we propose a model in which the occurrence of cysteine-rich positions is dictated by topological constrains, providing an explanation to why a degenerate pattern of cysteines can be achieved in a family of homologs. Thus, topological principles should enable the possibility to identify hidden regulatory cysteines that are not accurately detected using sequence based methodology.

Interplay between sequence, structure and linear motifs in the adenovirus E1A hub protein.

E1A is the main transforming protein in mastadenoviruses. This work uses bioinformatics to extrapolate experimental knowledge from Human adenovirus serotype 5 and 12 E1A proteins to all known serotypes. A conserved domain architecture with a high degree of intrinsic disorder acts as a scaffold for multiple linear motifs with variable occurrence mediating the interaction with over fifty host proteins. While linear motifs contribute strongly to sequence conservation within intrinsically disordered E1A regions, motif repertoires can deviate significantly from those found in prototypical serotypes. Close to one hundred predicted residue-residue contacts suggest the presence of stable structure in the CR3 domain and of specific conformational ensembles involving both short- and long-range intramolecular interactions. Our computational results suggest that E1A sequence conservation and co-evolution reflect the evolutionary pressure to maintain a mainly disordered, yet non-random conformation harboring a high number of binding motifs that mediate viral hijacking of the cell machinery.

Hidden Structural Codes in Protein Intrinsic Disorder.

Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and ß-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.

Degenerate cysteine patterns mediate two redox sensing mechanisms in the papillomavirus E7 oncoprotein.

Infection with oncogenic human papillomavirus induces deregulation of cellular redox homeostasis. Virus replication and papillomavirus-induced cell transformation require persistent expression of viral oncoproteins E7 and E6 that must retain their functionality in a persistent oxidative environment. Here, we dissected the molecular mechanisms by which E7 oncoprotein can sense and manage the potentially harmful oxidative environment of the papillomavirus-infected cell. The carboxy terminal domain of E7 protein from most of the 79 papillomavirus viral types of alpha genus, which encloses all the tumorigenic viral types, is a cysteine rich domain that contains two classes of cysteines: strictly conserved low reactive Zn+2 binding and degenerate reactive cysteine residues that can sense reactive oxygen species (ROS). Based on experimental data obtained from E7 proteins from the prototypical viral types 16, 18 and 11, we identified a couple of low pKa nucleophilic cysteines that can form a disulfide bridge upon the exposure to ROS and regulate the cytoplasm to nucleus transport. From sequence analysis and phylogenetic reconstruction of redox sensing states we propose that reactive cysteine acquisition through evolution leads to three separate E7s protein families that differ in the ROS sensing mechanism: non ROS-sensitive E7s; ROS-sensitive E7s using only a single or multiple reactive cysteine sensing mechanisms and ROS-sensitive E7s using a reactive-resolutive cysteine couple sensing mechanism.