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Comparison of RNAi screens for modifiers of protein misfolding diseases. A Venn diagram highlighting overlapping hits from other RNAi screens using models for diseases caused by protein aggregation or misfolding. Wang et al. (26) study ( A ), current study ( B ), Nollen et al. (22) study ( C ) and Lejune et al. (29) study ( D ). The details of each screen are summarized in Supplementary Material, Table S2. Numbers within parenthesis represent the total number of hits reported. Numbers not in parentheses represent number of overlapping hits with other screens. ∗ F48F7.1 ( alg-1 ); † C14B9.7 ( rpl-21 ), F42C5.1 ( rpl-8 ), Y46G5.4
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α1-Antitrypsin deficiency (ATD) is a common genetic disorder that can lead to end-stage liver and lung disease. Although liver
transplantation remains the only therapy currently available, manipulation of the proteostasis network (PN) by small molecule
therapeutics offers great promise. To accelerate the drug-discovery process for this disease, we...
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... of ATZ in live animals (20). Using a modification of this technology, we report here a semi-automated, genome-wide RNAi screen for proteostasis network (PN) disease modifiers of sGFP::ATZ accumulation. By using these PN modifiers to query target – ligand interaction databases, we developed a computational approach to identify new compounds that were effective in reducing ATZ accumulation in the C. elegans and a mammalian cell line overexpressing ATZ. This study demon- strated that a combination of genome-wide RNAi screens and in silico drug-discovery strategies provided a rapid and econom- ical means for preclinical drug repurposing for common as well as rare and neglected diseases, such as ATD. Genome-wide RNAi screens are powerful means of systematic- ally investigating genes that modulate biological processes (21). Previously, we developed a high-quality, HTS/HCS protocol for drugs that effect sGFP::ATZ accumulation in C. elegans (20). We adapted the assay to perform a semi-automated, genome- wide RNAi screen using the Arhinger feeding library (21). Our copy of the library contains Escherichia coli strains expressing double-stranded RNAs for 16 256 genes ( 500 of the original clones were eliminated due to annotation or technical errors (22)), which covers 85% of the C. elegans genome. The RNAi library was re-arrayed by chromosome number into 203 deep-well 96-well plates and an aliquot was removed for over- night growth and IPTG induction. One hundred transgenic sGFP::ATZ animals with similar fluorescence intensity were sorted into each well of a 96-well optical bottom assay plate along with a single bacterial RNAi clone for 48 h. Animals were immobilized and imaged utilizing the ArrayScan V TI . A flowchart outlining RNAi screen workflow, ArrayScan V TI images and development of a high quality single-well screening assay are summarized in Supplementary Material, Fig. S1A – K. Image capture and data analysis required 60– 80 min per 96-well plate. Assuming a 40 h workweek, a single person could screen the entire library of 17 000 clones in 20 days. For each RNAi sample on a plate, a z -score was calculated using a single plate sample-based method (see Materials and Methods). A total of 255 RNAi clones exceeded the arbitrary threshold of an absolute z -score . 2.35 (corresponding to a P , 0.05) and were selected for verification by a second round of testing (Fig. 1A and B). The second round of screening was completed in liquid culture as in the primary screen, except that: (i) RNAi samples were tested in triplicate wells ( n 1⁄4 100 animals/well), (ii) several vector(RNAi) control wells were included on each individual plate and (iii) each RNAi sample was assayed independently on 2 or more separate days. A two- tailed t -test identified individual RNAi sample well averages on each plate that were significantly different ( P , 0.05) from that of the corresponding vector(RNAi) controls (Fig. 1C – E). A total of 104 RNAi clones passed the secondary screen with 100 increasing and four decreasing sGFP::ATZ accumulation (Supplementary Material, Table S1). Since we inferred that the action of a wild-type gene was opposite to that of the RNAi effect (i.e. if gene A was a proteostasis enhancer and normally decreased sGFP::ATZ accumulation, gene A(RNAi) increased sGFP::ATZ accumulation), we arbitrarily classified the two groups of 100 and 4 PN modifier genes as ‘PN enhancers’ and ‘PN inhibitors’, respectively (Supplementary Material, Table S1). Transgenic C. elegans strains have been used to model aspects the cellular pathology of protein misfolding disorders associated with polyglutamine (polyQ) repeat sequences (e.g. Huntington’s disease) (23), a -synuclein mutants (e.g. Parkinson’s-like diseases) (24), tau mutants (e.g. frontotemporal dementia) (25) and superoxide dismutase (SOD1) mutants (e.g. amyotrophic lateral sclerosis) (26) (summarized in Supplementary Material, Table S2). Selected subset or genome-wide RNAi screens were conducted for PN modifiers, with the majority of RNAi clones exacerbating abnormal phenotypes or increasing the accumulation of the misfolded proteins (see Silva et al ., for a notable exception 27). Surprisingly, there was little overlap among PN modifier sets identified by these studies, although many of the studies identified genes associated with common GO biological processes (vide infra). To determine whether our set of PN modifiers overlapped with those from the other C. elegans screens, we employed a modified Fisher’s exact test (28). None of the gene lists from these RNAi screens showed a statistically significant overlap with our dataset. However, a total of eight PN modifiers from this study were detected in a least one of the three genome-wide RNAi screens for PN modifiers (Fig. 2; Supplementary Material, Table S2). These screens included two for polyQ-induced pathology in either body wall muscle or neurons (23,29), and one for mutant a -synuclein expression in neurons (26) (Fig. 2; Supplementary Material, Table S2). Notable in this group was genes involved in the RNAi pathway and protein synthesis. As a final test to ensure that common PN modifiers had not been overlooked due to the initial single-well assay format, we retested 30 different RNAi clones that were identified in at least two of the historical RNAi screens (Supplementary Material, Fig. S2). However, none of these RNAi clones altered steady-state levels of sGFP::ATZ. Taken together, these studies suggested that the PN modifiers regulating the cellular response to sGFP::ATZ were different from those associated with other aggregation prone-proteins, or that the PN pathways vary to a certain extent by the cellular (e.g. intestine, neuronal and muscle) and subcellular sites (e.g. ER, cytosolic) of misfolded protein accumulation. Enrichment of gene ontology (GO) terms significantly overre- presented in the 104 C. elegans PN modifier genes was assessed using the GOrilla web-based application (. technion.ac.il/) (30). We found no significant enrichment for any of the molecular function terms. Among the cellular compo- nent terms, only the intracellular part (GO:0044424) was overre- presented (1.7-fold) in comparison to a genome-wide control group of 11870 C. elegans genes with associated GO terms. However, the majority of enriched terms were associated with different developmental pathways, as might be expected from the high degree of development-related annotation in WormBase. To overcome this potential bias and to obtain data relevant to mammalian systems, the 104 C. elegans PN modifier genes were assigned human orthologs (Fig. 3A) utilizing two independent methods. First, we used WormBase (. WormBase.org; referential freeze WS236) to query the sequence names of the 104 PN modifier genes and identify the corresponding human orthologs with the highest pBLAST score and/or best predicted human ortholog (based on curated data from TreeFam, Inparanoid, Panther, EnsEMBL-compara ortholog prediction programs) (Supplementary Material, Table S1). Using this method, we found 77% (80 of 104) of the C. elegans genes to be orthologous to human genes (Fig. 3A and B). This high percentage of orthologous genes appeared to be typical (48 – 61%) of the gene sets accrued from RNAi PN modifier screens using other C. elegans models of proteotoxicity (24– 27). Second, we utilized the more stringent OrthoList compiled by Shaye and Greenwald (31), which is now available as an online tool via WormBase. The OrthoList was derived from a meta-analysis of 4 independent prediction methods, in order to generate a human ortholog list of 7663 C. elegans genes. Of the 104 C. elegans PN modifiers, 55 were found in OrthoList, yielding a match of 53% (Fig. 3A and B). While this was a lower matching rate compared with WormBase, it was still higher than the 35– 38% human orthologs predicted to be present in the C. elegans genome (31). Comparison of both the WormBase- and OrthoList-assigned human orthologs showed 90% overlap with a combined set of 85 genes (Fig. 3B; Supplementary Material, Table S1). These findings suggested that the RNAi screen for PN modifiers identified a proportionally higher percentage of evolutionary conserved genes. To compare the profiles of C. elegans PN modifiers to the human orthologs derived from WormBase and OrthoList, all three datasets were analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resource v6.7 (32). A functional annotation chart was generated using a term-centric singular enrichment analysis so that the protein profiles could be directly compared from C. elegans to humans (Fig. 3C). The corresponding donut chart shows overlap of the protein functional profiles, between C. elegans and humans. Comparison of functional categories between C. elegans PN modifiers and WormBase- and OrthoList-assigned genes showed 11/16 (68%) and 7/16 (43%) overlap, respectively. Consistent with 90% overlap in genes, overlap in 13/16 (81%) functional categories was seen between WormBase- and OrthoList-assigned human orthologs. Based on the examination of our PN modifier set using compara- tive analysis to other RNAi screens, pathway analysis and ortholog searches; no PN master gene set emerged with exception of a few known PN modifiers such as age-1 , ire-1 and daf-16 . Rather than further investigate the biologic activity of each new PN modifier, we sought to utilize the gene set as whole to serve as potential drug – target list and search for potential compounds that would be effective in decreasing sGFP::ATZ accumulation. The advantage of this approach is (i) prior knowledge of the gene function was not required, just whether the gene functioned as a PN enhancer or inhibitor in order to select an agonist or antagon- istic compound, respectively; (ii) the low cost and high proces- sivity of screening and validation in C. elegans ; (iii) selection of druggable targets from a gene ...
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... from sGFP::ATM- expressing animals, which facilitated the development of an automated high-throughput screening (HTS), high-content screening (HTS/HCS) assay for drugs that modulate the disposition of ATZ in live animals (20). Using a modification of this technology, we report here a semi-automated, genome-wide RNAi screen for proteostasis network (PN) disease modifiers of sGFP::ATZ accumulation. By using these PN modifiers to query target – ligand interaction databases, we developed a computational approach to identify new compounds that were effective in reducing ATZ accumulation in the C. elegans and a mammalian cell line overexpressing ATZ. This study demon- strated that a combination of genome-wide RNAi screens and in silico drug-discovery strategies provided a rapid and econom- ical means for preclinical drug repurposing for common as well as rare and neglected diseases, such as ATD. Genome-wide RNAi screens are powerful means of systematic- ally investigating genes that modulate biological processes (21). Previously, we developed a high-quality, HTS/HCS protocol for drugs that effect sGFP::ATZ accumulation in C. elegans (20). We adapted the assay to perform a semi-automated, genome- wide RNAi screen using the Arhinger feeding library (21). Our copy of the library contains Escherichia coli strains expressing double-stranded RNAs for 16 256 genes ( 500 of the original clones were eliminated due to annotation or technical errors (22)), which covers 85% of the C. elegans genome. The RNAi library was re-arrayed by chromosome number into 203 deep-well 96-well plates and an aliquot was removed for over- night growth and IPTG induction. One hundred transgenic sGFP::ATZ animals with similar fluorescence intensity were sorted into each well of a 96-well optical bottom assay plate along with a single bacterial RNAi clone for 48 h. Animals were immobilized and imaged utilizing the ArrayScan V TI . A flowchart outlining RNAi screen workflow, ArrayScan V TI images and development of a high quality single-well screening assay are summarized in Supplementary Material, Fig. S1A – K. Image capture and data analysis required 60– 80 min per 96-well plate. Assuming a 40 h workweek, a single person could screen the entire library of 17 000 clones in 20 days. For each RNAi sample on a plate, a z -score was calculated using a single plate sample-based method (see Materials and Methods). A total of 255 RNAi clones exceeded the arbitrary threshold of an absolute z -score . 2.35 (corresponding to a P , 0.05) and were selected for verification by a second round of testing (Fig. 1A and B). The second round of screening was completed in liquid culture as in the primary screen, except that: (i) RNAi samples were tested in triplicate wells ( n 1⁄4 100 animals/well), (ii) several vector(RNAi) control wells were included on each individual plate and (iii) each RNAi sample was assayed independently on 2 or more separate days. A two- tailed t -test identified individual RNAi sample well averages on each plate that were significantly different ( P , 0.05) from that of the corresponding vector(RNAi) controls (Fig. 1C – E). A total of 104 RNAi clones passed the secondary screen with 100 increasing and four decreasing sGFP::ATZ accumulation (Supplementary Material, Table S1). Since we inferred that the action of a wild-type gene was opposite to that of the RNAi effect (i.e. if gene A was a proteostasis enhancer and normally decreased sGFP::ATZ accumulation, gene A(RNAi) increased sGFP::ATZ accumulation), we arbitrarily classified the two groups of 100 and 4 PN modifier genes as ‘PN enhancers’ and ‘PN inhibitors’, respectively (Supplementary Material, Table S1). Transgenic C. elegans strains have been used to model aspects the cellular pathology of protein misfolding disorders associated with polyglutamine (polyQ) repeat sequences (e.g. Huntington’s disease) (23), a -synuclein mutants (e.g. Parkinson’s-like diseases) (24), tau mutants (e.g. frontotemporal dementia) (25) and superoxide dismutase (SOD1) mutants (e.g. amyotrophic lateral sclerosis) (26) (summarized in Supplementary Material, Table S2). Selected subset or genome-wide RNAi screens were conducted for PN modifiers, with the majority of RNAi clones exacerbating abnormal phenotypes or increasing the accumulation of the misfolded proteins (see Silva et al ., for a notable exception 27). Surprisingly, there was little overlap among PN modifier sets identified by these studies, although many of the studies identified genes associated with common GO biological processes (vide infra). To determine whether our set of PN modifiers overlapped with those from the other C. elegans screens, we employed a modified Fisher’s exact test (28). None of the gene lists from these RNAi screens showed a statistically significant overlap with our dataset. However, a total of eight PN modifiers from this study were detected in a least one of the three genome-wide RNAi screens for PN modifiers (Fig. 2; Supplementary Material, Table S2). These screens included two for polyQ-induced pathology in either body wall muscle or neurons (23,29), and one for mutant a -synuclein expression in neurons (26) (Fig. 2; Supplementary Material, Table S2). Notable in this group was genes involved in the RNAi pathway and protein synthesis. As a final test to ensure that common PN modifiers had not been overlooked due to the initial single-well assay format, we retested 30 different RNAi clones that were identified in at least two of the historical RNAi screens (Supplementary Material, Fig. S2). However, none of these RNAi clones altered steady-state levels of sGFP::ATZ. Taken together, these studies suggested that the PN modifiers regulating the cellular response to sGFP::ATZ were different from those associated with other aggregation prone-proteins, or that the PN pathways vary to a certain extent by the cellular (e.g. intestine, neuronal and muscle) and subcellular sites (e.g. ER, cytosolic) of misfolded protein accumulation. Enrichment of gene ontology (GO) terms significantly overre- presented in the 104 C. elegans PN modifier genes was assessed using the GOrilla web-based application (. technion.ac.il/) (30). We found no significant enrichment for any of the molecular function terms. Among the cellular compo- nent terms, only the intracellular part (GO:0044424) was overre- presented (1.7-fold) in comparison to a genome-wide control group of 11870 C. elegans genes with associated GO terms. However, the majority of enriched terms were associated with different developmental pathways, as might be expected from the high degree of development-related annotation in WormBase. To overcome this potential bias and to obtain data relevant to mammalian systems, the 104 C. elegans PN modifier genes were assigned human orthologs (Fig. 3A) utilizing two independent methods. First, we used WormBase (. WormBase.org; referential freeze WS236) to query the sequence names of the 104 PN modifier genes and identify the corresponding human orthologs with the highest pBLAST score and/or best predicted human ortholog (based on curated data from TreeFam, Inparanoid, Panther, EnsEMBL-compara ortholog prediction programs) (Supplementary Material, Table S1). Using this method, we found 77% (80 of 104) of the C. elegans genes to be orthologous to human genes (Fig. 3A and B). This high percentage of orthologous genes appeared to be typical (48 – 61%) of the gene sets accrued from RNAi PN modifier screens using other C. elegans models of proteotoxicity (24– 27). Second, we utilized the more stringent OrthoList compiled by Shaye and Greenwald (31), which is now available as an online tool via WormBase. The OrthoList was derived from a meta-analysis of 4 independent prediction methods, in order to generate a human ortholog list of 7663 C. elegans genes. Of the 104 C. elegans PN modifiers, 55 were found in OrthoList, yielding a match of 53% (Fig. 3A and B). While this was a lower matching rate compared with WormBase, it was still higher than the 35– 38% human orthologs predicted to be present in the C. elegans genome (31). Comparison of both the WormBase- and OrthoList-assigned human orthologs showed 90% overlap with a combined set of 85 genes (Fig. 3B; Supplementary Material, Table S1). These findings suggested that the RNAi screen for PN modifiers identified a proportionally higher percentage of evolutionary conserved genes. To compare the profiles of C. elegans PN modifiers to the human orthologs derived from WormBase and OrthoList, all three datasets were analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resource v6.7 (32). A functional annotation chart was generated using a term-centric singular enrichment analysis so that the protein profiles could be directly compared from C. elegans to humans (Fig. 3C). The corresponding donut chart shows overlap of the protein functional profiles, between C. elegans and humans. Comparison of functional categories between C. elegans PN modifiers and WormBase- and OrthoList-assigned genes showed 11/16 (68%) and 7/16 (43%) overlap, respectively. Consistent with 90% overlap in genes, overlap in 13/16 (81%) functional categories was seen between WormBase- and OrthoList-assigned human orthologs. Based on the examination of our PN modifier set using compara- tive analysis to other RNAi screens, pathway analysis and ortholog searches; no PN master gene set emerged with exception of a few known PN modifiers such as age-1 , ire-1 and daf-16 . Rather than further investigate the biologic activity of each new PN modifier, we sought to utilize the gene set as whole to serve as potential drug – target list and search for potential compounds that would be effective in decreasing sGFP::ATZ accumulation. The advantage of this approach is (i) prior knowledge of the gene function was not required, just whether the gene functioned as a PN enhancer or inhibitor in ...
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Alpha-1 antitrypsin deficiency (AATD) is a rare genetic disorder characterised by reduced levels of circulating alpha-1 antitrypsin and an increased risk of lung and liver disease. Recent reviews of AATD have focused on diagnosis, epidemiology and clinical management; comprehensive reviews examining disease burden are lacking. Therefore, we conduct...
Polymerization of the Z variant alpha-1-antitrypsin (Z-α1AT) results in the most common and severe form of α1AT deficiency (α1ATD), a debilitating genetic disorder whose clinical manifestations range from asymptomatic to fatal liver and/or lung disease. As the altered conformation of Z-α1AT and its attendant aggregation are responsible for pathogen...
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... STITCH integrates extensive data on protein interactions, pathways, and text-mining information, offering insights into the intricate network of chemical interactions, comprising a remarkable 1.6 billion interactions. Research by O'Reilly et al. exemplifies STITCH's utility in identifying potential drug targets for α1antitrypsin deficiency [51]. STITCH can also be queried for a set of chemicals to reveal possible targets, as demonstrated in the study by Kumar et al. which screened compounds capable of altering intracellular manganese levels [52]. ...
Computational methods have significantly transformed biomedical research, offering a comprehensive exploration of disease mechanisms and molecular protein functions. This article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease states. The utilization of protein/gene interaction and genetic variation databases, coupled with pathway analysis can facilitate the identification of potential drug targets. By bridging the gap between molecular-level information and disease understanding, this review contributes insights into the impactful utilization of computational methods, paving the way for targeted interventions and therapeutic advancements in biomedical research.
... Дефицит белка крови ингибитора α1-протеиназы, A1AT, является распространенным генетическим заболеванием, которое может привести к терминальной стадии заболевания печени и легких [18]. В настоящем исследовании уровень A1AT измеряли только у пациентов группы БА и ХОБЛ и в соответствующей группе К. Между группами больных и контролем статистически значимых различий в концентрации A1AT не было. ...
РЕЗЮМЕ
Выбор биомаркера (или нескольких биомаркеров) для диагностики заболевания или прогнозирования его исходов в когортном исследовании представляет собой отдельную проблему для исследователя. Для рационального выбора биомаркера важно определить валидный и невалидный биомаркер, задачу, на которую нацелен выбор биомаркера, и в зависимости от этого либо разработать дизайн исследования, либо включать в исследование биомаркер, который бы удовлетворял намеченному дизайну.
Цель исследования. Проиллюстрировать удачный и неудачный выбор биомаркера в рамках проведения когортного исследования.
Материал и методы. В исследование включены 283 участника обоих полов, из них 215 пациентов, у которых диагностировано одно из следующих заболеваний: 1) хроническая обструктивная болезнь легких (ХОБЛ) и бронхиальная астма (БА);
2) сахарный диабет (СД) 2-го типа; 3) неалкогольная жировая болезнь печени (НАЖБП); 4) артериальная гипертония (АГ).Контрольную группу (К) составили 68 здоровых добровольцев. В зависимости от группы в сыворотке крови определяли от 2 до 9 биомаркеров с помощью ИФА-наборов: N-оксид триметиламина (ТМАО), эозинофильный катионный белок (ECP), интерлейкины (IL) IL-4, IL-6, IL1-β, фактор некроза опухоли альфа (TNF-α), интерферон-гамма (IFN-γ), альфа1-антитрипсин (A1AT). Уровень липополисахарида (ЛПС, эндотоксина) определяли хромогенным методом Limulus Amebocyte Lysate (LAL).
Результаты. Взаимосвязь с изучаемыми нозологиями обнаружена для двух маркеров: ЛПС с СД и ТМАО с БА и ХОБЛ соответственно. При этом лишь LAL-тест на ЛПС валидирован FDA в качестве диагностического теста. Для остальных 7 биомаркеров не обнаружена статистически значимая взаимосвязь с изучаемыми нозологиями.
Заключение. Для получения информативных результатов рекомендуется тщательно координировать дизайн исследования и выбор биомаркера.
... Analogous to what has been observed in humans, the ATM model displayed normal secretion of the protein into the intestinal lumen, whereas the ATZ disease model developed protein accumulation in the ER as well as increased autophagy in these cells (Gosai et al., 2010). Given its faithful recapitulation of disease phenotypes, this ATD model was used in a high-throughput, genome-wide RNAi screen to identify genes that, when depleted, significantly affected ATZ accumulation in the intestine of these animals (O'Reilly et al., 2014;Wang et al., 2019). This screening strategy identified 54 modifier genes, which were also verified orthologs of human genes. ...
Although nearly 10% of Americans suffer from a rare disease, clinical progress in individual rare diseases is severely compromised by lack of attention and research resources compared to common diseases. It is thus imperative to investigate these diseases at their most basic level to build a foundation and provide the opportunity for understanding their mechanisms and phenotypes, as well as potential treatments. One strategy for effectively and efficiently studying rare diseases is using genetically tractable organisms to model the disease and learn about the essential cellular processes affected. Beyond investigating dysfunctional cellular processes, modeling rare diseases in simple organisms presents the opportunity to screen for pharmacological or genetic factors capable of ameliorating disease phenotypes. Among the small model organisms that excel in rare disease modeling is the nematode Caenorhabditis elegans. With a staggering breadth of research tools, C. elegans provides an ideal system in which to study human disease. Molecular and cellular processes can be easily elucidated, assayed and altered in ways that can be directly translated to humans. When paired with other model organisms and collaborative efforts with clinicians, the power of these C. elegans studies cannot be overstated. This Review highlights studies that have used C. elegans in diverse ways to understand rare diseases and aid in the development of treatments. With continuing and advancing technologies, the capabilities of this small round worm will continue to yield meaningful and clinically relevant information for human health.
... The employment of model organisms in high-throughput screening is viewed as a promising strategy to identify genes or drugs potentially relevant to health and fitness as well as to target key determinants in disease. In particular, the ability to generate large numbers of animals allied to high throughput observational measurement lends itself to the development of whole organism bioassays [10][11][12][13][14]. In the context of C. elegans, motility and to some extent feeding behaviour, have been successfully used strategies [15][16][17]. ...
Caenorhabditis elegans provides a multi-cellular model organism for toxicology and drug discovery. These studies usually require solvents such as dimethyl sulfoxide (DMSO), ethanol or acetone as a vehicle. This raises the need to carefully consider whether the chemical vehicles used in these screens are anodyne towards C. elegans. Here, we use pharyngeal pumping as a bioassay to assess this. Pharyngeal pumping is a visually scoreable behaviour that is controlled by environmental cues activating sensory and integrative neural signalling to coordinate pharyngeal activity. As such it serves as a rich bioassay to screen for chemical modulation. We found that while pumping was insensitive to high concentrations of the widely used drug solvents ethanol and acetone, it was perturbed by concentrations of DMSO above 0.5% v/v encompassing concentrations used as drug vehicle. This was manifested as an inhibition of pharyngeal pump rate followed by a slow recovery in the continued presence of the solvent. The inhibition was not observed in a neuroligin mutant, nlg-1, consistent with DMSO acting at the level of sensory processing that modulates pumping. We found that bus-17 mutants, which have enhanced cuticle penetration to drugs are more sensitive to DMSO. The effect of DMSO is accompanied by a progressive morphological disruption in which internal membrane-like structures of varying size accumulate. These internal structures are seen in all three genotypes investigated in this study and likely arise independent of the effects on pharyngeal pumping. Overall, these results highlight sensory signalling and strain dependent vehicle sensitivity. Although we define concentrations at which this can be mitigated, it highlights the need to consider time-dependent vehicle effects when evaluating control responses in C. elegans chemical biology.
... In the last few decades, there has been a surge in the number of autophagy-modulating drugs targeting these well-known autophagy regulators. For example, rapamycin that inhibits mTOR is known as one of the most important autophagy activators [15], and wortmannin which inhibits PI3K is known as a significant autophagy inhibitor [16,17]. In the meantime, autophagy modulation has been receiving increased attention as a strategy for developing therapeutics [18]. ...
Autophagy plays an essential role in cell survival/death and functioning. Modulation of autophagy has been recognized as a promising therapeutic strategy against diseases/disorders associated with uncontrolled growth or accumulation of biomolecular aggregates, organelles, or cells including those caused by cancer, aging, neurodegeneration, and liver diseases such as α1-antitrypsin deficiency. Numerous pharmacological agents that enhance or suppress autophagy have been discovered. However, their molecular mechanisms of action are far from clear. Here, we collected a set of 225 autophagy modulators and carried out a comprehensive quantitative systems pharmacology (QSP) analysis of their targets using both existing databases and predictions made by our machine learning algorithm. Autophagy modulators include several highly promiscuous drugs (e.g., artenimol and olanzapine acting as activators, fostamatinib as an inhibitor, or melatonin as a dual-modulator) as well as selected drugs that uniquely target specific proteins (~30% of modulators). They are mediated by three layers of regulation: (i) pathways involving core autophagy-related (ATG) proteins such as mTOR, AKT, and AMPK; (ii) upstream signaling events that regulate the activity of ATG pathways such as calcium-, cAMP-, and MAPK-signaling pathways; and (iii) transcription factors regulating the expression of ATG proteins such as TFEB, TFE3, HIF-1, FoxO, and NF-κB. Our results suggest that PKA serves as a linker, bridging various signal transduction events and autophagy. These new insights contribute to a better assessment of the mechanism of action of autophagy modulators as well as their side effects, development of novel polypharmacological strategies, and identification of drug repurposing opportunities.
... Following this precept paper supporting the development of autophagy enhancers to treat AATD liver disease, other autophagy enhancers have been identified on the basis of different animal models (C. elegans, mouse), but all these drugs need further validation of their efficacy in humans [47,[73][74][75][76]. ...
Human cells express large amounts of different proteins continuously that must fold into well-defined structures that need to remain correctly folded and assemble in order to ensure their cellular and biological functions. The integrity of this protein balance/homeostasis, also named proteostasis, is maintained by the proteostasis network (PN). This integrated biological system, which comprises about 2000 proteins (chaperones, folding enzymes, degradation components), control and coordinate protein synthesis folding and localization, conformational maintenance, and degradation. This network is particularly challenged by mutations such as those found in genetic diseases, because of the inability of an altered peptide sequence to properly engage PN components that trigger misfolding and loss of function. Thus, deletions found in the ΔF508 variant of the Cystic Fibrosis (CF) transmembrane regulator (CFTR) triggering CF or missense mutations found in the Z variant of Alpha 1-Antitrypsin deficiency (AATD), leading to lung and liver diseases, can accelerate misfolding and/or generate aggregates. Conversely to CF variants, for which three correctors are already approved (ivacaftor, lumacaftor/ivacaftor, and most recently tezacaftor/ivacaftor), there are limited therapeutic options for AATD. Therefore, a more detailed understanding of the PN components governing AAT variant biogenesis and their manipulation by pharmacological intervention could delay, or even better, avoid the onset of AATD-related pathologies.
... Furthermore, these platforms are adaptable for high throughput genetic and chemical screens to uncover autophagydependent disease modifiers. Autophagy inducers, 326,327 inhibitors, 328,329 and HLH-30/TFEB activators 106,330 have been uncovered through screens. These compounds may not only expedite drug discovery processes but can also be used in a reverse approach to understand the role of autophagy in various conditions. ...
Autophagy, originally described as a conserved bulk degradation pathway important to maintain cellular homeostasis during starvation, has also been implicated in playing a central role in multiple physiological processes. For example, autophagy is part of our innate immunity by targeting intracellular pathogens to lysosomes for degradation in a process called xenophagy. Coevolution and adaptation between viruses and autophagy have armed viruses with a multitude of strategies to counteract the antiviral functions of the autophagy pathway. In addition, some viruses have acquired mechanisms to exploit specific functions of either autophagy or the key components of this process, the autophagy-related (ATG) proteins, to promote viral replication and pathogenesis. In this chapter, we describe several examples where the strategy employed by a virus to subvert autophagy has been described with molecular detail. Their stratagems positively or negatively target practically all the steps of autophagy, including the signaling pathways regulating this process. This highlights the intricate relationship between autophagy and viruses and how by commandeering autophagy, viruses have devised ways to fine-tune their replication.
... A plate reader-based screen of a commercially available compound library yielded 33 compounds that decreased the rate of GFP-aggregation within the worms' intestinal cells 126 . More recently, a high-throughput genome-scale RNAi screen of ATZ model worms was performed to find gene inactivations that alter the intestinal GFPaggregation 127 . RNAi of 100 genes led to decreased levels of GFP-aggregation in the ATZ worms. ...
Deep phenotyping is an emerging conceptual paradigm and experimental approach aimed at measuring and linking many aspects of a phenotype to understand its underlying biology. To date, deep phenotyping has been applied mostly in cultured cells and used less in multicellular organisms. However, in the past decade, it has increasingly been recognized that deep phenotyping could lead to a better understanding of how genetics, environment and stochasticity affect the development, physiology and behavior of an organism. The nematode Caenorhabditis elegans is an invaluable model system for studying how genes affect a phenotypic trait, and new technologies have taken advantage of the worm's physical attributes to increase the throughput and informational content of experiments. Coupling of these technical advancements with computational and analytical tools has enabled a boom in deep-phenotyping studies of C. elegans. In this Review, we highlight how these new technologies and tools are digging into the biological origins of complex, multidimensional phenotypes.
... RNAi screen of ATZ model worms was performed a to find gene inactivations that alter the intestinal GFP-aggregation by the same group 116 . RNAi of 100 genes led to decreased levels of GFP-aggregation in the ATZ worms. ...
Deep phenotyping is an emerging conceptual paradigm and experimental approach that seeks to measure many aspects of phenotypes and link them to understand the underlying biology. Successful deep phenotyping has mostly been applied in cultured cells, less so in multicellular organisms. Recently, however, it has been recognized that such an approach could lead to better understanding of how genetics, the environment, and stochasticity affect development, physiology, and behavior of an organism. Over the last 50 years, the nematode Caenorhabditis elegans has become an invaluable model system for understanding the role of the genes underlying a phenotypic trait. Recent technological innovation has taken advantage of the worm physical attributes to increase the throughput and informational content of experiments. Coupling these technical advancements with computational or analytical tools has enabled a boom in deep phenotyping studies of C. elegans. In this review, we highlight how these new technologies and tools are digging into the biological origins of complex multidimensional phenotypes seen in the worm.
... Detectable differences in the Ex/Em spectra of individual FPs permit the visualization of multiple fluorophores within the same physical space (Table 1). Three FPs with different spectra, GFP (Ex488 nm/Em505 nm), YFP(Ex515 nm/Em526 nm) and mKate2(Em585 nm/Ex605 nm) [24][25][26], have been utilized in C. elegans within our laboratory [27,28]. To broaden our repertoire for multiplexing, we synthesized minigene gblocks for mOrange2, mNeptune2.5 and mCardinal2 [17,29]. ...
... Indeed, this functionality was demonstrated by a transgenic strain expressing human alpha-1 antitrypsin with the Z mutation fused to the Cterminus of GFP. This aggregation-prone protein, is retained in the ER and is partially degraded by macroautophagy [27,28,32,56]. Examination of these animals showed colocalization of ATZ in LGG-1 + (a C. elegans orthologue of LC3) structures (i.e., autophagosomes). ...
... For this reason, multifluorophore imaging in C. elegans can be a useful adjunct to the analysis of VUS, especially those associated with the subtle effects associated with protein misfolding. We showed that a mutation in the C. elegans ABC transporter, abt-4, resulted in ER retention, which is exactly what occurs in the human orthologous gene, ABCA3, with an identical mutation at a single conserved amino acid [57][58][59][60][61]. Similar results were observed in C. elegans expressing the human pathologic variant Z of alpha-1 antitrypsin [27,28,32]. Taken together, these studies show that the addition of CemOrange2 to the C. elegans FP toolbox expands their ability to assess human VUS behavior by multifluorophore, real-time subcellular imaging. ...
Due to its ease of genetic manipulation and transparency, Caenorhabditis elegans (C. elegans) has become a preferred model system to study gene function by microscopy. The use of Aequorea victoria green fluorescent protein (GFP) fused to proteins or targeting sequences of interest, further expanded upon the utility of C. elegans by labeling subcellular structures, which enables following their disposition during development or in the presence of genetic mutations. Fluorescent proteins with excitation and emission spectra different from that of GFP accelerated the use of multifluorophore imaging in real time. We have expanded the repertoire of fluorescent proteins for use in C. elegans by developing a codon-optimized version of Orange2 (CemOrange2). Proteins or targeting motifs fused to CemOr-ange2 were distinguishable from the more common fluorophores used in the nematode; such as GFP, YFP, and mKate2. We generated a panel of CemOrange2 fusion constructs, and confirmed they were targeted to their correct subcellular addresses by colocalization with independent markers. To demonstrate the potential usefulness of this new panel of fluorescent protein markers, we showed that CemOrange2 fusion proteins could be used to: 1) monitor biological pathways, 2) multiplex with other fluorescent proteins to determine colocalization and 3) gain phenotypic knowledge of a human ABCA3 orthologue, ABT-4, trafficking variant in the C. elegans model organism. © 2019 Thomas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
