Hsp70 molecular chaperones play a variety of functions in every organism, cell type and organelle, and their activities have been implicated in a number of human pathologies, ranging from cancer to neurodegenerative diseases. The functions, regulations and structure of Hsp70s were intensively studied for about three decades, yet much still remains to be learned about these essential folding enzymes. Genome sequencing efforts revealed that most genomes contain multiple members of the Hsp70 family, some of which co-exist in the same cellular compartment. For example, the human cytosol and nucleus contain six highly homologous Hsp70 proteins while the yeast Saccharomyces cerevisiae contains four canonical Hsp70s and three fungal-specific ribosome-associated and specialized Hsp70s. The reasons and significance of the requirement for multiple Hsp70s is still a subject of debate. It has been postulated for a long time that these Hsp70 isoforms are functionally redundant and differ only by their spatio-temporal expression patterns. However, several studies in yeast and higher eukaryotic organisms challenged this widely accepted idea by demonstrating functional specificity among Hsp70 isoforms. Another element of complexity is brought about by specific cofactors, such as Hsp40s or nucleotide exchange factors that modulate the activity of Hsp70s and their binding to client proteins. Hence, a dynamic network of chaperone/co-chaperone interactions has evolved in each organism to efficiently take advantage of the multiple cellular roles Hsp70s can play. We summarize here our current knowledge of the functions and regulations of these molecular chaperones, and shed light on the known functional specificities among isoforms.

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BackgroundThe cytosol of most eukaryotic cells contains multiple highly conserved Hsp70 orthologs that differ mainly by their spatio-temporal expression patterns. Hsp70s play essential roles in protein folding, transport or degradation, and are major players of cellular quality control processes. However, while several reports suggest that specialized functions of Hsp70 orthologs were selected through evolution, few studies addressed systematically this issue.Methodology/Principal FindingsWe compared the ability of Ssa1p-Ssa4p from Saccharomyces cerevisiae and Ssa5p-Ssa8p from the evolutionary distant yeast Yarrowia lipolytica to perform Hsp70-dependent tasks when expressed as the sole Hsp70 for S. cerevisiae in vivo. We show that Hsp70 isoforms (i) supported yeast viability yet with markedly different growth rates, (ii) influenced the propagation and stability of the [PSI+] and [URE3] prions, but iii) did not significantly affect the proteasomal degradation rate of CFTR. Additionally, we show that individual Hsp70 orthologs did not induce the formation of different prion strains, but rather influenced the aggregation properties of Sup35 in vivo. Finally, we show that [URE3] curing by the overexpression of Ydj1p is Hsp70-isoform dependent.Conclusion/SignificanceDespite very high homology and overlapping functions, the different Hsp70 orthologs have evolved to possess distinct activities that are required to cope with different types of substrates or stress situations. Yeast prions provide a very sensitive model to uncover this functional specialization and to explore the intricate network of chaperone/co-chaperone/substrates interactions.

Animal behavior is increasingly being recorded in systematic imaging studies that generate large data sets. To maximize the usefulness of these data there is a need for improved resources for analyzing and sharing behavior data that will encourage re-analysis and method development by computational scientists 1 . However, unlike genomic or protein structural data, there are no widely used standards for behavior data. It is therefore desirable to make the data available in a relatively raw form so that different investigators can use their own representations and derive their own features. For computational ethology to approach the level of maturity of other areas of bioinformatics, we need to address at least three challenges: storing and accessing video files, defining flexible data formats to facilitate data sharing, and making software to read, write, browse, and analyze the data. We have developed an open resource to begin addressing these challenges using worm tracking as a model.To store video files and the associated feature and metadata, we use a Zenodo.org community (an open-access repository for data) that provides durable storage, citability, and supports contributions from other groups. We have also developed a web interface that enables filtering based on feature histograms that can return, for example, fast and curved worms in addition to more standard searches for particular strains or genotypes ( Fig. 1 and http://movement.openworm.org/). The database consists of 14,874 single-worm tracking experiments representing 386 genotypes (building on 9,203 experiments and 305 genotypes in a previous publication 2 ) and includes data from several larval stages as well as ageing data consisting of over 2,700 videos of animals tracked daily from the L4 stage to death. Full resolution videos are available in HDF5 containers that include gzip-compressed video frames, timestamps, worm outline and midline, feature data, and experiment metadata. HDF5 files are compatible with multiple languages including MATLAB, R, Python, and C. We have also developed an HDF5 video reader that allows video playback with adjustable speed and zoom (important when reviewing high-resolution, multi-worm tracking data), as well as toggling of worm segmentation over the original video to verify segmentation accuracy during playback.Secondly, we have defined an interchange format named Worm tracker Commons Object Notation (WCON), to facilitate data sharing and software reuse among groups working on worm behavior. WCON uses the widely supported JSON format to store tracking data as text that is both human and machine readable. It is compatible with single and multi-worm 3 data, at any resolution: from a single point representing worm position over time 4 , to many points representing the high-resolution skeleton of a moving worm 2 . Importantly, it also supports custom feature additions so that individual labs can store their own specific data sets alongside the universal set of basic worm data. WCON readers are available for Python, MATL...

The yeast Saccharomyces cerevisiae has been used as a model for fungal biofilm formation due to its ability to adhere to plastic surfaces and to form mats on low-density agar petri plates. Mats are complex multicellular structures composed of a network of cables that form a central hub from which emanate multiple radial spokes. This reproducible and elaborate pattern is indicative of a highly regulated developmental program that depends on specific transcriptional programming, environmental cues, and possibly cell-cell communication systems. While biofilm formation and sliding motility were shown to be strictly dependent on the cell-surface adhesin Flo11p, little is known about the cellular machinery that controls mat formation. Here we show that Hsp70 molecular chaperones play key roles in this process with the assistance of the nucleotide exchange factors Fes1p and Sse1p and the Hsp40 family member Ydj1p. The disruption of these cofactors completely abolished mat formation. Furthermore, complex interactions among SSA genes were observed: mat formation depended mostly on SSA1 while minor defects were observed upon loss of SSA2; additional mutations in SSA3 or SSA4 further enhanced these phenotypes. Importantly, these mutations did not compromise invasive growth or Flo11p expression, suggesting that Flo11p-independent pathways are necessary to form mats.

The enzyme TDO (tryptophan 2,3-dioxygenase; TDO-2 in Caenorhabditis elegans) is a potential therapeutic target to cancer but is also thought to regulate proteotoxic events seen in the progression of neurodegenerative diseases. To better understand its function and develop specific compounds that target TDO we need to understand the structure of this molecule. In C. elegans we compared multiple different CRISPR/Cas9-induced tdo-2 deletion mutants and identified a motif of three amino acids (PLD) that is required for the enzymatic conversion of tryptophan to N-formylkynurenine. Loss of TDO-2’s enzymatic activity in PDL deletion mutants was accompanied by an increase in motility during aging and a prolonged lifespan, which is in line with the previously observed phenotypes induced by a knockdown of the full enzyme. Comparison of sequence structures suggests that blocking this motif might interfere with haem binding, which is essential for the enzyme’s activity. The fact that these three residues are situated in an evolutionary conserved structural loop of the enzyme suggests that the findings can be translated to humans. The identification of this specific loop region in TDO-2–essential for its catalytic function–will aid in the design of novel inhibitors to treat diseases in which the TDO enzyme is overexpressed or hyperactive.

Ageing affects a wide range of phenotypes at all scales, but an objective measure of ageing remains challenging, even in simple model organisms. To measure the ageing process, we characterized the sequence of alterations of multiple phenotypes at organismal scale. Hundreds of morphological, postural, and behavioral features were extracted from high-resolution videos. Out of the 1019 features extracted, 896 are ageing biomarkers, defined as those that show a significant correlation with relative age (age divided by lifespan). We used support vector regression to predict age, remaining life and lifespan of individual C. elegans. The quality of these predictions (age R 2 = 0.79; remaining life R 2 = 0.77; lifespan R 2 = 0.72) increased with the number of features added to the model, supporting the use of multiple features to quantify ageing. We quantified the rate of ageing as how quickly animals moved through a phenotypic space; we quantified health decline as the slope of the declining predicted remaining life. In both ageing dimensions, we found that short lived-animals aged faster than long-lived animals. In our conditions, for isogenic wild-type worms, the health decline of the individuals was scaled to their lifespan without significant deviation from the average for short-or long-lived animals.

In its natural habitat, C. elegans encounters a wide variety of microbes, including food, commensals and pathogens. To be able to survive long enough to reproduce, C. elegans has developed a complex array of responses to pathogens. These activities are coordinated on scales that range from individual organelles to the entire organism. Often, the response is triggered within cells, by detection of infection-induced damage, mainly in the intestine or epidermis. C. elegans has, however, a capacity for cell non-autonomous regulation of these responses. This frequently involves the nervous system, integrating pathogen recognition, altering host biology and governing avoidance behaviour. Although there are significant differences with the immune system of mammals, some mechanisms used to limit pathogenesis show remarkable phylogenetic conservation. The past twenty years have witnessed an explosion of host-pathogen interaction studies using C. elegans as a model. This review will discuss the broad themes that have emerged and highlight areas that remain to be fully explored. Natural environment and microbiotaCaenorhabditis elegans is a small free-living nematode found worldwide, predominately in humid, temperate areas where it can feed on the bacteria that proliferate on decaying vegetation (Schulenburg and Félix, 2017). Its natural environment comprises a complex community of microbes, including bacteria, fungi and viruses, including many parasitic species. The effect of environmental microbes on worm fitness can be beneficial, detrimental or mixed (Khan et al., 2018). And as the same microorganism can sometime be either beneficial or detrimental depending on the environmental conditions or the genotype of the host (Gravato-Nobre et al., 2020;Zarate-Potes et al., 2020), we will use the terms of "pathogen" or "commensal" for a given microbe as a simplification.A broad range of microorganisms can infect nematodes in a variety of ways. Different fungi, for example, have independently acquired the capacity to infect worms using diverse strategies (Lebrigand et al., 2016). Some species capture their prey with adhesive structure such as Arthobotrys oligosora or elegant mechanical traps like the constricting rings of al., 2001). Apart from recognition of viral replication products by DRH-1/RIG-1 (Ashe et al., 2013), see below, examples of direct microbial detection that lead to immune pathway activation remain elusive in C. elegans (Kim and Ewbank, 2018).Various molecules from the host, such as the protein HMGB1, formylated peptides, mitochondrial DNA, or uric acid, amongst many others, can also trigger innate immune activity (Tang et al., 2012). Matzinger and colleagues recognized that cells are agnostic with regard to the origin of the damage signals and will respond to them regardless of the preceding event, which led to the 'damage-associated molecular pattern' or DAMP hypothesis (Matzinger, 2002;Seong and Matzinger, 2004). On this basis, the field of innate immunity widened to include recognition of both non-self and se...