Mage = 22.14 years, SDage = 4.82 years) who completed five response time tasks and self-reported symptoms of ADHD using the Conners’ Adult ADHD Rating Scale was used. Principal components analysis (PCA) on these response time measures  produced two variability factors (labelled response selection and selective attention). To understand the genetic drivers of IIRTV we performed a genome-wide association analysis (GWAS) on these PCA-derived indices of IIRTV. For the selective attention variability factor, we identified one single-nucleotide polymorphism (SNP) attaining genome-wide significance; rs62182100 in the HDAC4 gene located on chromosome 2q37. A bootstrapping mediation analysis demonstrated that the selective attention variability factor mediated the relationship between rs62182100 and self-reported ADHD symptoms. Our findings provide the first evidence of a genome-wide significant SNP association with IIRTV and support the potential utility of IIRTV as a valid endophenotype for ADHD symptoms. However, limitations of this study suggest that these observations should be interpreted with caution until replication samples become available.Intra-individual response time variability (IIRTV) is proposed as a viable endophenotype for many psychiatric disorders, particularly attention-deficit hyperactivity disorder (ADHD). Here we assessed whether IIRTV was associated with common DNA variation genome-wide and whether IIRTV mediated the relationship between any associated loci and self-reported ADHD symptoms. A final data set from 857 Australian young adults (489 females and 368 males;  In ADHD, increased IIRTV has been suggested as a leading endophenotype that is able to index the underlying genetic risk for the disorder10. Several behavioural genetic studies have revealed the heritable nature of intra-individual variability, driven largely by additive genetic influences12. Rather than simply representing a non-specific marker of brain dysfunction, IIRTV has been associated with neurobiological networks of attention15. Indeed, neuroimaging studies in both adolescents and adults suggest that IIRTV is related to task-dependent activations of the anterior cingulate and medial prefrontal cortex, dorsolateral prefrontal cortex, and posterior parietal cortex16. Collectively, these findings have led to the proposition that IIRTV arises from the involvement of two processing streams; a top-down attentional control process whereby IIRTV results from spontaneous fluctuations in attentional demand, or a bottom-up process wherein IIRTV develops due to disruptions of the “default mode” network of the brain, comprising regions that are typically deactivated during goal-orientated response time (RT) tasks18.A hallmark of neurocognitive disturbance in many neurological and psychiatric disorders is an increase in intra-individual variability in response time (IIRTV). This increase has been observed across a range of cognitive tasks and disorders, including strokeDAT1, DRD4, SLC6A2 and ADRA2A in cohorts of individuals with and without ADHD22 the additive genetic influences of IIRTV have yet to be explored in a genome-wide manner.Despite growing support for both a genetic and neurobiological basis of IIRTV, its specific genetic architecture remains largely unknown. Although a small number of candidate gene studies have identified associations with catecholamine system genes such as The aim of the present study was to perform a genome-wide association study (GWAS) of IIRTV in a general population sample of young adults. Specifically, we explored IIRTV across a range of neurocognitive measures of RT performance, and conducted principal component analyses (PCAs) to reduce the dimensionality of the RT data into two components, representative of response selection and selective attention, respectively. We then performed a genome-wide association analysis on these PCA-derived indices of IIRTV to identify novel sources of genetic variation contributing to IIRTV. Finally, we explored the association between our PCA-derived indices of IIRTV and self-reported ADHD symptoms, and examined whether the former mediated the relationship between individual genetic variants associated with IIRTV and self-reported ratings of ADHD symptoms. Using this methodology, we identify the first genetic locus associated with IIRTV at a genome-wide level.23. Ethical approvals were granted by both the University of Queensland and Monash University ethics committees. All participants provided informed consent before completing a battery of five cognitive RT tasks and self-reporting ADHD symptoms using the long version of the Conners’ Adult ADHD Rating Scales (CAARS-S:L)24. Saliva samples for genetic analysis were obtained from participants using Oragene kits , and DNA was isolated from those according to standard protocols.One thousand two hundred and ninety-six control participants with no self-reported personal history of psychiatric or neurological disorders were recruited for the present study. Participants were recruited from Melbourne and Brisbane, Australia. To control for genetic variation amongst ethnic populations all participants were of European ancestry as determined by self-report of the ancestry of all four grandparents25, where participants provided either a ‘left’ or ‘right’ response to a target arrow located centrally on a computer screen, while discounting four flanking distractors ; (4) a spatial competition task, which required participants to indicate the orientation of a target letter (an upright or inverter letter ‘T’), while ignoring competing distractors  locations from amongst rival distractors , which provides a measure of response-time variability that controls for differences in the baseline speeds of processing14. Full details of the above tasks have previously been reported22.For all cognitive tasks, stimuli were presented on an 85 Hz, 12 × 16-inch cathode ray tube monitor positioned at a viewing distance of 65 cm  away from the participant. Participants were instructed to align their visual gaze onto a centrally positioned fixation cross (+) and to make their responses using a standard computer keyboard. Five cognitive tasks were completed in counterbalanced order: (1) an Eriksen flanker taskors Fig. ; (2) a cors Fig. ; (3) a sors Fig. ; (5) a Pors Fig. . Across 2, age × sex, testing site, and the top two eigenvectors for the underlying population sub-structure. A genome-wide significance threshold of 5 × 10−8 was adopted to adjust for multiple comparisons. Linkage disequilibrium (LD) analysis was subsequently performed for our lead SNP using PLINK v1.929, and were plotted using Haploview 4.130A GWAS was performed to test for an association between our PCA-derived indices of IIRTV and individual genetic variants (imputed SNPs) using a linear regression model that assumed an additive model of genetic inheritance. Regression models were adjusted for age, sex, age31. To assess the influence of IIRTV as an endophenotype of ADHD symptoms we utilised the Preacher and Hayes32 bootstrapping macro in SPSS to bootstrap the sampling distribution of the indirect effect, where the indirect effect corresponds to a reduction in the strength of the gene/ADHD symptom association that is attributed to IIRTV. Bootstrapping estimates were based on 100,000 bootstrap samples.In the current study, we tested a mediational model of an endophenotype, which assumes that the causal path from gene to disorder/trait passes through an endophenotypeMage = 22.14 years, SDage = 4.82 years).A stringent quality control process was conducted on all task and genotypic data (see Supplementary Information). After quality control, the remaining sample comprised of 857 subjects  and 37.2% and 19.38% (Brisbane) of the variance, respectively. Oblimin rotation35 was performed and revealed the presence of a simple structure, with our measure of ICV showing strong loadings and all task variables loading substantially to either one of two components (similarly for our measure of SD RT).For the SD and ICV RT data derived for each of the five response time tasks, PCA was performed separately across each testing site (Melbourne and Brisbane). Given the intrinsic correlation between measures of SD and ICV RT data, the analyses and results are presented for ICV only . For each PCA by site, the correlation matrices consisted of multiple coefficients above 0.3. Bartlett’s test of sphericity22.ICV from the Flanker, Go and Stop tasks loaded very strongly on component 1 (hereafter factor 1), while ICV from the Competition and Cueing tasks loaded very strongly on component 2  IV Inattention; DSM IV Hyperactivity/Impulsivity; and ADHD Index) as assessed by the CAARS  IV Inattention; DSM IV Hyperactivity/Impulsivity; and ADHD Index) as assessedby the CAARS : rs62182100 within the HDAC4 gene . The imputation quality (r2) for rs62182100 is 0.51382—meeting the recommended INFO imputation quality score standard of 0.3 suggested to define sufficiently good imputation quality38, with a minor allele frequency of 0.05525. Comparable results were found for the measure of SD of RT , we identified one imputed SNP that attained genome-wide significance  are open access and available under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License.GWAS summary statistics for this study . This indicates more significant associations between genetic variants and IIRTV than expected by chance alone. The inflation factor of the test statistic for ICV factor 2 (λ = 1.01) revealed minimal inflation, suggesting little influence of population stratification or other systematic biases. LD analysis of our genome-wide significant SNP (rs62182100) identified three surrounding variants  with our lead SNP . As can be seen from Fig. To examine the addictive effect of the association between the 24. The indirect effect of rs62182100 on the different self-reported ADHD symptom measures via factor 2 ICV are summarised in Table We also assessed the influence of IIRTV as an endophenotype of ADHD symptomatology by evaluating whether any of the PCA-derived indices of IIRTV mediated an association between genetic variation in the genome-wide significant SNP rs62182100) and measures of self-reported ADHD symptoms 82100 and12. Here we have identified the first genetic locus associated with increased IIRTV through genome-wide analysis in a sample of healthy young adults. Further, we have also demonstrated that IIRTV mediates the relationship between the identified genetic variants present in the HDAC4 gene and self-reported symptoms of ADHD.Increased intra-individual response time variability is characteristically reported across a range of heritable neurological and psychiatric disorders. In disorders of attention, particularly ADHD, an increase in IIRTV is thought to be endophenotypic, indexing underlying genetic riskHDAC4 gene and IIRTV. The HDAC4 gene belongs to a class of histone deacetylase (HDAC) genes and encodes HDAC439, which has been implicated in the indirect inhibition of DNA transcription40 through modulation of promoter activity41. HDACs play a pivotal role in the regulation of transcription factors by moderating their access to DNA41. Animal studies have previously implicated HDACs in the modulation of memory43, learning, and synaptic plasticity44, and pharmacological research has demonstrated that the administration of HDAC inhibitors lead to improvements in learning and memory45. Importantly, HDAC4 is strongly expressed in the brain, being broadly expressed in the cortex and hippocampus46. Selective loss of HDAC4 in the brain has been shown to result in impairments in spatial learning and long-term synaptic plasticity and spatial learning44. Although no study to date has directly implicated HDAC4 in specific attentional processes, and given our lead SNP (rs62182100) lies within this gene, the relevant activity of this family of enzymes warrants further investigation within the context of attentional processes.This study reports for the first time a genetic association between DNA variation in the 49. Second, the observation that IIRTV mediates the relationship between DNA variation in the HDAC4 gene and ADHD symptoms in healthy young adults, provides critical support for a mediational model of an endophenotype, under which genetic liability for a trait  passes through the endophenotype31. Third, the fact that we identified our association with the “selective attention” and not “response selection” IIRTV factor is interesting. The cognitive tasks loading on the selective attention factor require participants to filter distractors and focus on task-relevant stimuli, which maps conceptually to subjective reports of “distractibility” in ADHD.The results of this study are noteworthy for a number of reasons. First, to our knowledge it is the first study to employ a genome-wide approach to isolate the genetic substrates of IIRTV. Previous studies, including our own, have performed surveys of a limited number of candidate genes with mixed results50)—will be needed to advance the field. One could argue that if IIRTV is an endophenotype for ADHD then genes linked to this trait should emerge as risk genes for ADHD more broadly. However, a simple look-up in the latest ADHD GWAS meta-analysis performed by the Psychiatric Genomics Consortium and Danish IPSYCH group51 found no evidence of association with either rs62182100 or the three SNPs in LD  within HDAC4. Also, although one other study52 has recently reported cross-disorder evidence of association (p = 7.65 × 10−6) for rs3791556 located within the HDAC4 gene and five major psychiatric disorders (including ADHD) the associated SNP (rs3791556) is not in LD with the SNP associated with IIRTV in this study. Interestingly, HDAC4 has been implicated in functional genetic pathway analyses, with the class of histone methylation processes  reportedly showing the strongest association of genetic expression related to the adult disorders 53. These observations suggest that our genome-wide findings should be interpreted with caution until replication samples become available. Indeed, we also note that we previously published a candidate gene association with IIRTV in a subset of the current sample  and found an association with the SNPs in the ADRA2A gene and ICV factor 1 (response selection) (rs1800544 and rs602618)22. We do not, however find any consistent evidence for this association in the current genome-wide analysis in the sample of 857 young adults .Nonetheless, there are a number of limitations to this study. First, our study is underpowered to detect reliable genome-wide discovery signals and lacked a replication sample. We suggest that a consortium approach to cognitive genetics—much like that used for imaging genetics (e.g., ENIGMAHDAC4 gene and to mediate the relationship between this genetic variant of the HDAC4 gene and self-reported ADHD symptoms. Although these data provide further support for the primacy of a response time variability endophenotype for ADHD symptoms, they require replication in larger cohorts.In summary IIRTV captured by PCA-derived indices of response time variability were found to be associated with a genetic variation in the Supplementary Material


NEFL mRNA. In order to complete the understanding of altered NF expression in ALS, in this study we have investigated the regulation of NEFM and NEFH mRNA levels by miRNAs. We observed that a small group of ALS-linked miRNAs that are expressed in human spinal motor neurons directly regulate NEFM and NEFH transcript levels in a manner that is associated with an increase in NFM and NFH protein levels in ALS spinal cord homogenates. In concert with previous observations demonstrating the suppression of NEFL mRNA steady state levels in ALS, these observations provide support for the hypothesis that the dysregulation of miRNAs in spinal motor neurons in ALS fundamentally alters the stoichiometry of NF expression, leading to the formation of pathological NCIs.Neurofilaments (NFs) are the most abundant cytoskeletal component of vertebrate myelinated axons. NFs function by determining axonal caliber, promoting axonal growth and forming a 3-dimensional lattice that supports the organization of cytoplasmic organelles. The stoichiometry of NF protein subunits  has to be tightly controlled to avoid the formation of NF neuronal cytoplasmic inclusions (NCIs), axonal degeneration and neuronal death, all pathological hallmarks of amyotrophic lateral sclerosis (ALS). The post-transcriptional control of NF transcripts is critical for regulating normal levels of NF proteins. Previously, we showed that miRNAs that are dysregulated in ALS spinal cord regulate the levels of  Neurofilaments (NFs) are unique neuron-specific intermediate filaments in vertebrates. They are highly dynamic structures that determine axonal caliber, promote axonal growth and organize the cytoplasm to form a stable 3-dimensional lattice that supports the organization of organelles and cytoplasmic proteins , 2.NF subunit proteins  form homo- and hetero-polymers following a specific stoichiometry and tight spatiotemporal regulation. Conserving NF stoichiometry by controlling the levels of expression of individual NF subunits is critical for the maintenance of healthy neurons. Alterations of NF mRNA steady stoichiometry and the associated formation of neuronal cytoplasmic inclusions (NCIs) composed of NF proteins are neuropathological markers of degenerating motor neurons in amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease –4. AlthoNEFL mRNA stability [NEFL mRNA levels observed in ventral lateral spinal cord motor neurons in ALS [NEFM and NEFH mRNA stability are however unknown. In this study we observed that a limited number of ALS-linked miRNAs that are expressed in spinal motor neurons directly regulate NEFM and NEFH mRNA levels, in a way that might explain the increase in NFM and NFH protein levels that we observed in ALS spinal cords and thus contribute directly to the formation of NF NCIs.Post-transcriptional control is crucial for preserving NF subunit expression in neuronal homeostasis and also during axonal outgrowth in development and regeneration –8. MiRNAtability , and poss in ALS , 14. Pros in ALS  and the s in ALS . The miRSOD1, TARDBP, FUS or expanded repeats in C9orf72  and age-matched, neuropathologically healthy control individuals  were used. All ALS cases were both clinically and neuropathologically confirmed using the El Escorial Criteria . Written consent for autopsy was obtained from the next of kin at the time of death or from the patient antemortem in accordance with the London Health Sciences Centre consent for autopsy. ALS cases were genotyped and confirmed to have no known mutations in NEFM and NEFH mRNA 3’UTRs were obtained using 3’RACE PCR. Briefly, TRIzol reagent (Thermo Fisher Scientific) was used for total RNA extraction from human spinal cord tissue. 3’RACE PCR was performed using SMARTer RACE 5′/3’ RACE Kit  and primers hNEFM_3RACE_F1D: 5’CACTTCACACGCCATAGTAAAGGAAGTCACC3′ and hNEFH_3RACE_F2: 5’GAGAAGGCCACAGAAGACAAGGCCGCCAAG3’ for NEFM and NEFH 3’UTRs, respectively. 3’UTR isoforms were cloned into pGEMT-Easy vector and sequenced. For luciferase assays, 3’UTRs were subcloned into pmirGLO vector between NheI and SalI sites and linked to the firefly luciferase coding region. Mutations in two nucleotides at the 3’end of each miRNA recognition element (MRE) within the NEFM and NEFH 3’UTRs were made using QuikChange Site-Directed Mutagenesis Kit II (Agilent) according to the manufacturer’s instructions. Mutations were carefully designed to ensure no changes were made in the secondary structures of the transcripts using the RNAFold WebServer (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi). Both TargetScan (http://www.targetscan.org/) and miRanda (http://www.microrna.org/microrna/getGeneForm.do) software programs were used to determine miRNAs with predicted MREs in either NEFM or NEFH 3’UTRs.Total miRNA extraction using the mirVana miRNA isolation kit (Thermo Fisher Scientific) was performed from human ventral lumbar spinal cord using 5 controls and 8 ALS tissue samples according to the manufacturer’s instruction. Yield and purity of the miRNA solution was determined using spectrophotometry while RNA integrity was measured using a bioanalyzer instrument.-ΔΔCT. All experiments were run in triplicate and significance was determined using Student’s t-test.MiRNA extracts from the spinal cord of ALS patients or controls were reversed transcribed and then subjected to real-time PCR using the miRCURY LNA™ Universal RT microRNA PCR (Exiqon) and ExiLENT SYBR Green master mix (Exiqon), according to the manufacturer’s instructions. PCRs were performed using the 7900 HT real-time PCR system. Relative expression of miRNAs was normalized to miR-16-5p, a miRNA previously demonstrated to have the same expression in sALS and controls [NEFM and NEFH mRNA, total RNA extraction was performed on 6 ALS patient and 6 control lumbar spinal cord samples using TRIzol reagent . RNA samples were subjected to a cDNA synthesis reaction using the SuperScript IV VILO reverse transcriptase  in accordance to the manufactures instructions. Real-time PCR was done on the cDNA templates using the TaqMan Fast Advanced Master Mix and TaqMan Gene Expression Assays  targeting either NEFM or NEFH. Assays were performed in accordance to the manufactures instructions. TaqMan probes which either targeted NEFM or NEFH were designed with a FAM fluorophore. The expression of NEFM and NEFH were normalized to the expression of a reference gene (HPRT1), which was targeted by a TaqMan probe containing a VIC fluorophore. Changes in NEFM and NEFH mRNA expression between ALS patients and control subjects were determined using the ΔΔCT method, where fold-change was calculated as 2-ΔΔCT. Experiments were run in triplicate and determined to be significantly different using a Student’s t-test.To examine the expression levels of To ensure that the miRNAs of interest are expressed in human motor neurons, neuropathologically normal lumbar spinal cord from control subjects was examined for miRNA expression. Tissue sections were formalin-fixed, paraffin embedded (FFPE) and cut into 7 μm sections. Samples were UV treated overnight to reduce the lipofuscin-induced auto-fluorescent signal. FISH was performed as described previously . LNA probes were designed with double DIG-labels that targeted the miRNA of interest (Exiqon). DIG-HRP secondary antibody, and Tyramide Signal Amplification (TSA) Systems tagged with a Cy3 fluorophore (PerkinElmer) were used to obtain a fluorescent signal of the miRNA target. Ventral horn of human lumbar spinal cord tissue was examined for positive staining within motor neurons using the Olympus FV1000 confocal microscope.2. HEK293T cells were plated on 96-well plates with a density of 10,000 cells/well 24 h prior to transfection. 100 nM of miRNA mimics (Thermo Fisher Scientific) and 3.47 fmol of pmirGLO containing NEFM or NEFH 3’UTR were co-transfected into the cells using Lipofectamine 2000 reagent (Thermo Fisher Scientific).HEK293T cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM) containing 10% fetal bovine serum (FBS), at 37 °C with 5% COt-test or one-way ANOVA followed by Turkey’s post hoc test.Luciferase assays and relative quantitative RT-PCR were performed 24 h post-transfection as was described previously . Data sht-test was used to determine statistical differences in endogenous protein expression.Total protein extraction from ventral lumbar spinal cord of 3 controls and 6 ALS patients was performed using NP40 lysis buffer containing proteinase inhibitors. Samples were sonicated, resuspended in loading buffer, denatured at 90 °C and run on an 8% SDS-gel. After transfer, the nitrocellulose membrane was probed with either mouse anti-NFM , mouse anti-NFH , or rabbit anti-GAPDH  and later with HRP-secondary antibody . Relative protein expression of NFM and NFH were normalized to GAPDH expression levels. Student’s NEFM and NEFH mRNAs are expressed in human spinal cord. A single variant form of NEFM and NEFH 3’UTRs  was detected in lumbar spinal cord control tissue .Considering that 3’UTR polymorphisms have been increasingly reported in the literature, we determined if 3’UTR variants of sue Fig. . AnalysiNEFM and NEFH 3’UTRs have multiple MREs for different pools of miRNAs. However, for this study we only considered those miRNAs that we previously observed to be differentially expressed in ALS tissue versus controls using the TaqMan assay [NEFM or NEFH 3’UTRs  and Rho Guanine Nucleotide Exchange Factor  mediate the destabilization and TAR DNA binding protein 43 kDa (TDP-43) the stabilization of NEFL mRNA [NEFL, NEFM and NEFH transcripts [mRNA stability is the regulatory process of NF transcripts most extensively studied in which multiple trans-acting factors participate. In mice, it has been shown that the RNA-binding protein p190RhoGEF stabilizes and that glycolytic isoenzymes aldolases A and C directly destabilizes EFL mRNA , 23. OurEFL mRNA –26. In anscripts .NEFL mRNA [NEFM and NEFH post-transcriptional regulation. We created a list of miRNAs that are down-regulated in ALS spinal cord and that also possess MREs within NEFM and NEFH 3’UTRs. From the published literature, we observed that two miRNAs of this group (miR-9 and miR-125b-5p) were confirmed to be reduced in ALS spinal cord [NEFM and NEFH mRNA levels, an effect that is translated into a reduction of NFM and NFH protein levels within spinal cord homogenates. From this group of miRNAs that regulate NEFM and NEFH mRNA levels, only miR-9 has been reported to have a role in neuronal function. More specifically, by regulating several targets including OC1, FoxP1, MAP1B, and MCPIP1, miR-9 is critical for motor neuron development, function and survival [The most prominent mechanism of RNA mediated gene silencing involves the interaction of miRNAs with their target mRNAs in which most, but not all, interactions between the miRNA and MREs leads to a degradation of the mRNA. Previously, we and others have observed a massive down-regulation of miRNAs in ALS spinal cord , 12, 17.EFL mRNA . In thisnal cord , 12. We survival .NEFM and NEFH transcripts in ALS ventral lumbar spinal cord homogenates that we observed here using real-time PCR and reported previously using RNase protection assay [As these group of miRNAs that regulate NFM and NFH are reduced in spinal cord of ALS tissue, we predicted that the net effect would be an increase of NFM and NFH protein levels in ALS-spinal cords. Several groups have shown that NFL, NFM and/or p-NFH levels are increased in biological fluids of ALS patients –33, but on assay .NEFL steady state mRNA levels in spinal motor neurons of ALS patients has been well documented [NEFL-linked miRNAs [NF transcripts in a manner that induces an alteration in the stoichiometry of the individual NF proteins, favoring the formation of pathological NCIs.A selective reduction of cumented , 14, 35,d miRNAs . In concWhile this hypothesis supports the critical role of the alteration of miRNA expression in ALS, miRNAs alone are not the sole mediators of RNA stability. Indeed, understanding the fundamental relationship between alterations in RNA-binding proteins and how this interacts with alterations in miRNAs expression will be critical to understanding the process of perturbed RNA-mediated gene silencing which appears to lie at the core of a majority of ALS cases.


Mus musculus and Pipistrellus pipistrellus brain and skeletal muscle. Fatty acid binding protein 3 was found at different levels in mouse and bat muscle mitochondria and its orthologues were investigated in Caenorhabditis elegans knock-downs for LBP 4, 5 and 6. In the bat, high levels of free fatty acids and N-acylethanolamine lipid species together with a significantly greater abundance of fatty acid binding protein 3 in muscle  were found. Manipulation of fatty acid binding protein orthologues in C. elegans suggest these proteins and their role in lipid regulation are important for mitochondrial function.It is accepted that smaller mammals with higher metabolic rates have shorter lifespans. The very few species that do not follow these rules can give insights into interesting differences. The recorded maximum lifespans of bats are exceptional - over 40 years, compared with the laboratory mouse of 4 years. We investigated the differences in the biochemical composition of mitochondria between bat and mouse species. We used proteomics and ultra-high-performance liquid chromatography coupled with high resolution mass spectrometry lipidomics, to interrogate mitochondrial fractions prepared from  Recent figures indicate that 21% of the world’s population will be aged 60 or over by 2050 .The rate of living theory of ageing proposes to explain the variation in mammalian lifespans, it states that lifespan and metabolic rate are inversely correlated . Mic. MicThe ifespans . For ins 4 years . Bats ha 4 years . This raMyotis lucifugus), shrews (Blarina brevicauda) and white-footed mice (Peromyscus leucopus). Bats were found to produce half to one third of the amount of hydrogen peroxide per oxygen molecular consumed compared to both shrews and mice [Oxidative stress has been a key focus for the majority of studies investigating longevity in bats. Mitochondrial dysfunction is evident in ageing and age-related diseases. Mitochondrial DNA (mtDNA) is considered to be more susceptible to mutagenesis due to the close proximity of mtDNA to ROS and also the high number of direct repeat regions (8-10 bp) which are prone to deletions . Bat mtDand mice . Researcand mice .M.lucifugus remains unchanged [Hibernation has also been suggested to contribute to longevity in bats, however, when comparing the life span of non-hibernating bats to non-flying eutherian mammals, bats still live on average 7 years longer . Interesnchanged . Deterionchanged –19. StudPipistrelle bats  with parallel sample types prepared from young and middle-aged Mus musculus [An active mitochondrial population is considered to be an intrinsic cellular requirement for healthy ageing. Loss of mitochondrial functionality has been implicated in neurodegenerative diseases as well as in age related sarcopenia ,20. Prevmusculus ,22.p<0.05). Whilst, ATP synthase subunit d, NADH dehydrogenase flavoprotein 2, NADH dehydrogenase iron-sulphur protein 3, RAB14, myelin basic protein and Ras-related protein are each significantly relatively more abundant in the mouse brain mitochondrial proteome (p<0.05). We measured more ATP synthase subunit d (2 fold) in the mouse brain mitochondrial proteome in comparison to the bat (p=0.0001). Mitoprot probability scores for mitochondrial import are calculated for spot numbers 194, 180, 174, 173 and 74. The proteins identified from these spots have sequence motifs that support a localisation in the mitochondrial compartment.We wished to gauge whether the biochemical composition of mitochondria in bat brain is markedly different to mitochondria in the mouse brain. We report the top nine proteins that have significantly different relative quantities when comparing the bat and mouse brain mitochondrial proteomic profiles . QuantitWe have highlighted the top six proteins that have significantly different relative quantities when comparing the bat and mouse skeletal muscle mitochondrial proteomes . ATP synPyruvate dehydrogenase E1 component subunit beta is significantly more abundant in the mouse skeletal muscle mitochondria by a fold change of 2.5. Pyruvate dehydrogenase E1 component subunit beta is a mitochondrial protein and the cleaved sequence is included . Fatty ap = 0.037)  .Many of the differences between mitochondria when comparing bat with mouse were in proteins associated with the electron transport chain. We wanted to know whether these differences grossly change the function of complex 1. We measured complex 1 activity in muscle and brain mitochondria from each species. Though in each tissue the complex 1 activity was found to be lower in the mouse the differences were not significant .species can now be added to age and tissue type as a determinant of mitochondrial lipid profile [Previously we have reported that mitochondrial lipid profiles are tissue and age specific . We wish profile .Having confirmed that there are differences in the lipid composition of the bat compared with mouse mitochondria, we focused on the lipids that had the greatest discrepancies between the two mammals. We identified the top 10 lipids with greatest overall fold change between bat and mouse brain mitochondria . We alsoWe looked to see whether any particular groups of lipids could be associated with one species or the other. Several N-acylethanolamine species were found in both the top ten muscle and brain lists . In everp<0.05)  .Skeletal muscle lipids follow a similar trend where 36 of the 43 identified fatty acids are more abundant in the bat mitochondria compared to the mouse . Of the C. elegans. Sequence homology and phylogeny confirm their similarity to FABP3  in regulating mitochondrial lipids and thereby lifespan. This work was done in the nematode worm to facilitate monitoring of lifespan changes. We identified fatty acid binding protein orthologues in to FABP3 . RNAi knto FABP3 . MeasureTM) and oxygen consumption rates measured at different ages. The knock-downs all had a higher oxygen consumption rate when compared with controls. Controls exhibited a higher oxygen consumption rate as they grew older and therefore the mutants have a more similar phenotype to the aged control specimens  were used for the LBP4, 5 and 6 knock-down experiments. We visualised the worms alongside controls to compare mitochondrial morphology . With eaWe set out to examine mitochondrial compositional differences between the mouse and relatively long-lived pipistrelle bat. To focus our study, we examined enriched mitochondrial fractions extracted from whole brain and skeletal muscle, these were chosen as tissue types that decline in performance with age and are likely to exhibit lifespan regulated changes. The different metabolic nature of these tissues can give us a broader view of age-related mitochondrial changes.Identification of proteins that are present in different relative quantities when comparing mouse and bat suggested mitochondrial electron transport chain components are interesting in this context. The electron transport chain proteins are the machinery for generating ATP and changes in these molecules could be postulated to alter the efficiency of intracellular energy production. In brain mitochondria we also found significant differences in two RAS oncogene family RAB proteins 1B and 14, these are GTPases involved in intracellular trafficking between Golgi and endosomes ,27, therTo examine mitochondrial lipid differences between bat and mouse we used ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry to separate and identify lipid contents of mitochondrial fractions from brain and muscle. Ceramide (32:1), N-acylethanolamines (18:2 and 22:6) and a docosanoid species were identified within the top six lipid species, each more abundant in the bat mitochondrial fractions. We noticed that lipid species known to be metabolic precursors of lipid mediators of inflammatory processes, particularly the N-acylethanolamines, DPA, DHA and AA are found to be highly abundant in bat mitochondria when compared with young or older mouse mitochondrial lipids ,35. ThisC. elegans, an animal model that has been used extensively to study pathways important in ageing [C. elegans [In order to interrogate the effect of free fatty acids upon mitochondrial health we interrogated FABP orthologues  in the nematode worm n ageing ,40. We w elegans . Our kno elegans . We sugg elegans . In huma elegans . In musc elegans .Gad67 [Gad67 is upregulated in the retina of the Klotho knockout mouse model of accelerated ageing [Fabp3 in non-cardiac tissues is further supported by work in the klotho knockout mouse, where significantly decreased levels of Fabp3 are measured in the submandibular salivary gland [It has been shown that polyunsaturated fatty acids (PUFAs) are essential for brain development and function. Increasing evidence shows that an imbalance of PUFAs is associated with psychiatric disorders, including autism and schizophrenia. Fabp3 KO mice have cognitive and emotional deficits and FABP3 regulates GABA synthesis through transcriptional regulation of Gad67 . Interesd ageing . The impry gland .We show that decreased quantities of FABP3 orthologues are detrimental to mitochondrial health. The literature supports this as a mechanism associated with mitochondrial dysfunction across many tissues. Mechanisms to increase levels of FABP3 or fatty acids in the mitochondrial compartment may be of interest in supporting mitochondrial health through the lifespan.This study has been approved by the School of Veterinary Medicine and Science Ethics and Clinical Review Panel, University of Nottingham (ERN# 1922 170103). All mouse tissues were obtained from Charles River Laboratories. Mice were humanely killed by a trained individual using an approved schedule 1 method, in full accordance with UK Home Office guidelines. Human brain tissues were obtained  from the Parkinson’s UK Brain Bank in London.Natural England. It was important to ensure that tissues from the bats were obtained in good condition for our biochemical analyses. Bat carcasses were frozen as soon as possible after death and transported on dry ice to the laboratory where mitochondrial extractions were performed. Tissue integrity for the bat tissues was confirmed for another study where high >8 RIN (RNA integrity) values were obtained for RNA extracted from these bat samples. Charles River Laboratories. Mice were humanely killed by a trained individual using an approved schedule 1 method, in full accordance with UK Home Office guidelines. The mitochondrial fraction was isolated by differential centrifugation from the tissues as previously described [Bat tissues were obtained from animals that had died at the hospital from natural causes and adult individuals were selected for likely older age by an experienced hospital bat handler based on previous observations that older adults have a rougher coat condition with thinning patches and other general signs such as tattered wing and ear skin. Bat carcasses were obtained from the West Yorkshire Bat Hospital with permission from escribed .Pipistrellus pipistrellus bats (>12 months old). , old C57BL/6J mice (78 weeks old) (Charles River) and from adult Mitochondrial fractions were prepared from mouse brain tissue (young 4-11 weeks old n=10 and old 78 weeks n=10), mouse skeletal muscle tissue (young 4-11 weeks n=10 and old 78 weeks n=10), adult bat brain (n=10) and adult bat skeletal muscle tissue (n=10). 100 μl of chloroform/methanol (2:1) was added to each sample and extracted for 20 min using a multiplace vortex before undergoing centrifugation  at 4°C. The supernatants were removed to HPLC vials. Isopropanol (50 μl) was added to each vial before lipidomics analysis.Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS) was performed on the mitochondrial lipid extracts (10 µL injection volume) using an Accela LC coupled with an Exactive mass spectrometer  in positive and negative electrospray ionisation modes (ESI).ccls4251  I; him-8 (e1489) IV) with GFP fusion proteins localised to mitochondria and nuclei [CB5600  was used for the analysis of oxygen consumption upon knockdown of LBP-4, -5 and -6 across the lifespan of adult Total fatty acid concentration was measured using the Free Fatty Acid Quantification Kit , according to manufacturer’s instructions. Briefly, 4 plates of cleaned adult age day 0 worms were suspended in chloroform/Triton X-100 (1% Triton X-100) and homogenised by 30 strokes of a 1.5ml mini-pestle, vortexed and centrifuged at 16,000g for 10 min. Lower phases of the samples were collected and vacuum dried for 30 min. Reported concentrations were quantified by fluorometric analysis (Varioskan LUX Multimode Microplate Reader).Supplementary File


Oral Squamous Cell Carcinoma (OSCC) patients respond poorly to chemotherapy. We analyzed the expression of 11 drug response-related genes in 31 OSCC biopsies, collected prior to any treatment, using custom-designed PCR array. Further, we investigated the drug response pattern of selected anticancer drugs by BH3 (Bcl2 Homology-3) profiling in the primary cells isolated from OSCC tissues. Then, we correlated the results of drug-response gene expression pattern with apoptotic priming to predict tumor response to chemotherapy. The best performing drug (BPD) and response differences (RD) between the drugs were identified using statistical methods to select the best choice of drug in a personalized manner. Based on the correlation, we classified OSCC tumors as sensitive (13 tumors), moderately responsive (16 tumors) or resistant (2 tumors) to chemotherapy. We found that up-regulation of genes linked with drug resistance facilitates survival of tumor samples, which was revealed by the percentage of apoptotic priming. Moreover, we found that paclitaxel-induced 40–45% apoptotic priming compared to other drugs. Average response difference (RD) analysis showed that 80% of tumors responded well to paclitaxel as compared to other drugs studied. Therefore, gene expression analysis with BH3 profiling reveals drug sensitivity that could be translated for drug selection before treatment. Annually 130,000 people succumb to oral cancer in this country which translates into approximately 14 deaths per hour3. Oral cancers include malignant neoplasms found on the lip, floor of the mouth, cheek lining, gingiva, palate or tongue. Oral Squamous Cell Carcinoma (OSCC) account for more than 90% of all oral malignant lesions5. It has been demonstrated that a large number of OSCC patients show poor response to chemotherapeutic drugs8. The clinical drug response of a cancer sub-type seems to be mediated by several mechanisms. These drug response mechanisms include overexpression of membrane transporters effluxing anticancer drugs from the cells, activation of DNA repair enzymes, defects in proteins involved in cell cycle analysis and apoptosis and activation of cytosolic drug detoxification12.Oral cancer is a major public health issue, which is responsible for 3–10% of cancer mortality worldwide. The Indian subcontinent accounts for one-third of the world oral cancer burden and the oral cancer ranks among the top three types of cancer in India13. A significant challenge in various fields of medicine is to assign a drug that will be advantageous14. In oncology, this decision has generally been driven by the anatomic location and histology of the tumor. For some time, therapeutic decision making was assisted by cytogenetics, immunohistochemical and flow cytometric analysis of cell surface antigens14. However, the forecasters, such as histological grade and lymph node status, would often fail to classify precisely their clinical behavior15. Recently, the availability of techniques of gene expression profiling has allowed establishing the relationship between gene expression and drug sensitivity in tumor cells16. In the clinical setting, an array of genes has been identified as potential predictive markers of drug activity and their use could be progressively implemented for drug selection in patients receiving chemotherapy, thus allowing more rational and individualized treatments17. This type of approach has been initiated with in vitro systems by the National Cancer Institute (NCI) in Bethesda, Maryland (USA) and is pursued by a growing number of public and private laboratories around the world17. Although extensive research has been performed under in vitro conditions concerning drug response and many of the mechanisms have been characterized, translating this to the clinic still represents a major conceptual and technical challenge. Hence, an additional approach that identifies drug sensitivity could significantly advance the clinical management of tumors such as OSCC. Analyzing the expression patterns of genes related to drug response in tumor samples along with evaluating drug response at the cellular level using cell-based assays will assist in drug selection in a personalized manner in order to manage OSCC.Ethnic, genetic and epigenetic dissimilarities within clonal populations can determine whether a specific drug combination will benefit a patient or instigate resistance18. Recently, a new functional assay, BCL2-homology domain 3 (BH3) profiling, was reported, and this profiling could predict drug sensitivity in primary tumor samples19. The BH3 profiling is a potentially powerful technique to measure early changes in net pro-apoptotic signaling in mitochondria (“apoptotic priming”) induced by chemotherapeutic agents14. BH3 profiling interrogates the BCL-2 family of proteins that regulates commitment to the mitochondrial pathway of apoptosis in response to most chemotherapeutic agents20. BH3 peptides are convenient, titratable components that can be exploited to systematically study mitochondrial readiness to undergo apoptosis21. Thus, BH3 profiling based on the drug’s ability to initiate apoptosis priming can be used to predict the cytotoxic response of cancers to chemotherapeutics before chemotherapy is administered.The BCL-2 family proteins are known to control the apoptosis and classified into pro-apoptotic and anti-apoptotic membersThere is a significant lack of scientific investigation correlating expression pattern of genes involved in drug response with cell-based experiments to precisely forecast tumor sensitivity towards anticancer drugs. To satisfy this unmet need, we correlated certain drug-response related gene expression patterns with the % apoptotic priming in cancer cells isolated from a cohort of OSCC samples. In this study, we employed a qRT-PCR array to study the expression of certain multidrug resistance (MDR)-linked genes and correlated this with the results of BH3 profiling (percent of apoptotic priming) in order to understand the drug response pattern in a cohort of 31 OSSC tumor specimens.Fresh oral tumor biopsies were obtained by routine resections after patients signed an informed consent from Rajah Muthiah Dental College, Annamalainagar. Patients who had already undergone chemotherapy or radiation therapy were excluded from this study. The obtained tumor samples were divided into two parts; (i) for the study of MDR gene expression analysis and (ii) for the analysis of BH3 profiling. For MDR related gene expression studies the tumor biopsies were transferred to sample collection tubes containing RNAlater stabilization reagent. For BH3 profiling the primary tumor cells were isolated and cell viability was assessed by a trypan blue dye exclusion test before actual experiments were performed . The informed consent was obtained from all subjects. Clinical data and tumor samples were collected according to the approved ethical guidelines.4 cells/well) for 4 h and the % apoptotic priming was analyzed using BH3 profiling method.Tissue samples were collected in a sterile tube containing serum-free medium with 1% penicillin-streptomycin-fungizone. The samples were then finely minced by surgical blades after washing with saline. Finely minced tissues were incubated at 37 °C with collagenase for 3–5 h. After incubation, collagenase activity was blocked by the addition of medium with 10% FBS. The solution was then centrifuged at 2000 rpm for 6 min. The cell pellets were resuspended in complete medium and incubated at 37 °C in a 5% CO2 incubator. Equal concentrations of drugs (1 μM) i.e., paclitaxel, doxorubicin, daunorubicin, vincristine and vinblastine were treated in the isolated primary tumor cells  on an Eppendorf RealPlex instrument. The fold changes of gene expression were analyzed and plotted as clustergram using the SA Biosciences PCR array data analysis online tool . Relative gene expression (RQ) was calculated using 2−∆∆Ct.The total RNA content of the cells was isolated from tumor tissues using an RNeasy mini kit  according to the manufacturer’s instructions and stored at −80 °C until used for gene expression by qRT-PCR arrays. The purity of the freshly isolated total RNA was measured by Nanodrop (Thermo Scientific) and total RNA was employed for the gene expression analysis. The cDNA was reverse transcribed from RNA using a First Strand cDNA Synthesis Kit (Qiagen reverse transcriptase kit). The relative expression pattern of genes related to drug resistance , apoptosis (TP53), transcription factors (STAT5B and LRP1) and cell cycle regulation (CDKN1A and CDK2) were analyzed by a PCR array using RTThe BH3 profiling was performed in tumor tissue samples using BIM peptide (BCL-2-interacting mediator of cell death) to predict drug sensitivity. The BIM peptide was synthesized by the Fmoc solid-phase peptide synthetic strategy and characterized by HPLC and mass spectroscopy .All analyses were carried out using measurements taken in triplicate. Statistical analyses were performed by one-way ANOVA to determine significant differences between groups at P < 0.05. Pearson correlations were tested for significance (by two-tailed unpaired t-test) at the same confidence limit. The Statistical Package, IBM SPSS Version 21), R programming version 3.3.2 and Microsoft Excel 2007  were used for the statistical and graphical evaluations. To apply linear prediction to the dataset, R programming version 3.3.2 was used. To indicate the response to the drugs, Equations  was conducted to know whether the MDR-linked gene expression and % apoptotic priming were influenced by gender difference , which were found to be highly progressive histologically  and fourth quartile  were tumors with low expression levels of ABCB1 that could be sensitive to anticancer treatment. Similarly, drug response could be easily predicted based on the pattern of expression of other drug response genes  in the tumor samples i (1 to 31). Figure 40. The Ct-values of drug response linked gene expression and % apoptotic priming were analyzed by the PAM algorithm and the tumors were clustered as sensitive, moderately responsive and resistant  were also found to be resistant to anticancer therapy. The tumor samples which were generally not showing any drug resistance gene expression  were found to be sensitive to chemotherapeutic drugs. The mitochondrial apoptotic priming during drug treatment in tumor samples 3, 6, 12, 13 and 22 were found to be only partial Fig. . It shou42  have revealed a set of differentially methylated DNA regions which were replicated in 60–90% cohort of Indian OSCC patients45. In this study, we observed low R-Square value (0.3331) and high p-value (0.5875), which questions the reliability of this linear prediction model. The confidence level of the drug of choice prediction based on 31 tumor samples was only 33%. Therefore, to confirm the drug of choice for this OSCC population the number of tumor samples may be increased so that the personalized choice of drug for oral cancer patients could be more accurately predicted. Previously, there were number of studies illustrating drug prediction based on the small sample number. Montero et al.14 employed 24 bone marrow primary chronic myeloid leukemia samples to predict imatinib response and 16 ovarian adenocarcinoma samples to predict carboplatin response using BH3 profiling14. Burger et al.46 analyzed the mRNA expression levels of BCRP, LRP, MRP1, MRP2 and MDR1 based on 59 breast tumor samples46. Li Su et al.47 examined the association between the MDR1 gene of gastrointestinal tumors and resistance to chemotherapeutic drugs using 38 colon cancer samples, 46 esophageal cancer samples and 42 gastric cancer samples47. Though, the number of samples in this study was only 31, the present findings can be applicable to OSCC when we further account other clinical features like age, sex, tumor grade, tumor stage and clinical staging of the patients. Analyzing these multiple clinical and experimental features using statistical methods like multilinear regression (MLR), MLR-Log and Least Square Method (LSM) will precisely predict the drug response before therapy.The linear prediction has previously been employed to identify the most effective chemotherapy drug based on MDR-linked gene expression dataAccording to the present findings, correlation of MDR-linked gene expression pattern with the results of BH3 apoptotic profiling can be a potential predictive strategy to identify the best drug option among many therapeutic drugs available for OSCC patients. It is important to note that we used tissue samples collected prior to any treatment; thus, reveals the biological status of tumors which will assist in the selection of drug of choice to a patient in a personalized manner.Supplementary Files


Piezo1 is a mechanosensitive (MS) ion channel with characteristic fast-inactivation kinetics. We found a slowly-inactivating MS current in mouse embryonic stem (mES) cells and characterized it throughout their differentiation into motor-neurons to investigate its components. MS currents were large and slowly-inactivating in the stem-cell stage, and became smaller and faster-inactivating throughout the differentiation. We found that Piezo1 is expressed in mES cells, and its knockout abolishes MS currents, indicating that the slowly-inactivating current in mES cells is carried by Piezo1. To further investigate its slow inactivation in these cells, we cloned Piezo1 cDNA from mES cells and found that it displays fast-inactivation kinetics in heterologous expression, indicating that sources of modulation other than the aminoacid sequence determine its slow kinetics in mES cells. Finally, we report that Piezo1 knockout ES cells showed a reduced rate of proliferation but no significant differences in other markers of pluripotency and differentiation. PIEZO1 gene that cause slow inactivation have recently been associated with hereditary xerocytosis, a disorder of ionic imbalance in red blood cells  and the broad timescales in which they operate suggest the existence of equally complex underlying transduction machineries. The recent identification of a structurally unique family of mechanosensory ion channels, the Piezos , and theod cells . These dNotably, multiple cell lines exhibit a variety of undescribed stretch-activated currents that differ from Piezos in their kinetics. For example, dorsal root ganglia cells display three types of mechanosensory ionic currents when directly stimulated with a probe: rapid-, intermediate-, and slow-inactivating currents . Piezo2 We found a large mechanosensitive current in mouse embryonic stem cells with distinctively slow-inactivating kinetics that resembles currents present in C2C12 cells and slow-inactivating DRGs. In addition to a self-standing interest in identifying slow-inactivating mechanosensory components, we found its presence in stem cells particularly interesting. Although not part of a mechanosensory organ, stem cells are extremely alert to environmental cues. Multiple reports show that the cellular fate of multipotent stem cells can be influenced by mechanical strain, shear stress, substrate stiffness or elasticity . Given tWe describe in this manuscript a large mechanosensitive, slowly-inactivating current in mouse embryonic stem cells. We investigated the evolution of this stem cell mechanosensory current along a model differentiation pathway into motor neurons, and found it to be carried by Piezo1.We screened multiple cell lines searching for slow inactivating mechanosensitive (MS) currents using the ‘poking’ assay . In thisCa > PK = PNa> PNMDG  there was no significant difference in the organization of mESC colonies, expression of pluripotency transcription factors (SOX2), typical cell-to-cell or cell-to-substrate adhesions , or size of colonies , Table 1We next tested several stages of early differentiation. When ‘naïve’ mESC cultures were converted to the next developmental stage, ‘primed,’ epiblast-like stem cells (EpiSC), no change in marker expression or colony organization was observed between genotypes . GastrulPiezo1 gene. The identity of this MS current is therefore unequivocally assigned to Piezo1. Less clear is why embryonic stem cells would express high levels of a mechanosensitive ion channel. Until recently, growth factors were the most recognized factor influencing stem cells homeostasis and differentiation. However, recent reports have begun to show that mechanical cues are also able to sharply affect stem cell fate. For example, mechanical properties of the growth substrate can modulate the lineage choice of neural stem cells  or from mechanical properties of the particular cellular environment, or a combination of both. It is interesting to note that the mRNA expression of  neurons  correlat neurons . In lighWe still know very little about modulation of Piezo1 behavior. In a recent work, Bae et al showed that the kinetics of human PIEZO1 can be regulated by pH . AdditioLastly, it is likely that other unknown mechanosensory ion channels exist. The Patapoutian group reported that only the fast-inactivating component of the mechanosensory currents in DRG neurons can be attributable to Piezo2 . Piezo1 Overall Piezo1 KO ES cell lines showed minimal changes in pluripotency or differentiation in vitro compared to wild type lines. This finding fits with the normal early development reported for Piezo1 KO mice. However, outside of the lethal ~e14 vascularization defect reported for these mice, little specific or functional phenotyping was done, leaving open the possibility of subtle functional defects occurring early in development, which may be compensated by homeostatic developmental mechanisms. Based on functional channel expression during pluripotency and early differentiation, we originally hypothesized that Piezo1-mediated mechanoreception in epiblast cells would affect early development. This hypothesis was based on the crucial but poorly defined role for mechanical forces in the tissue morphogenesis, which establishes and defines gastrulation, as well as in vitro studies using mouse and human ES cells . Our finHEK293 tsA201 cells were obtained from Sigma and maintained in DMEM (Gibco) supplemented with 10% Fetal Bovine Serum (Gibco) and 1% L- Glutamine (Gibco). Mouse embryonic stem cells (Hb9-GFP) were obtained from the Wichterle lab . This ceFor electrophysiological recordings of mouse embryonic stem cells, cells were plated on 12 mm poly-D-lysine coated coverslips (NeuVitro), pre-coated with Matrigel (Invitrogen). Mouse embryonic stem cells normally grow forming tight associations called embryonic bodies that prevent patch clamp procedures. In order to facilitate electrophysiological recordings, cells were dissociated to single-cell level using Accutase (Gibco) or Trypsin (Gibco) and plated at low density  in the presence of Rho-K inhibitor (Millipore). MS currents were recorded ~4–10 hr after plating. For electrophysiological recordings of Day 5 and Day 7 cells, coverslips were coated with PDL and Laminin EHS.For differentiating mouse embryonic stem cells into motor neurons we followed protocols by the Wichterle lab , but repAll poking experiments were performed using a probe drawn from borosilicate glass (Sutter Instruments) fire polished  until sealed. The probe was mounted to piezo-driven actuator driven by a controller/amplifier  controlled through Clampex software. After formation of a whole-cell seal by a different electrode, the probe was positioned at 60° to the cell ∼2 µm away from the membrane.All pressure applications through patch pipettes were performed with a high- speed pressure clamp (ALA Scientific) controlled through Clampex software. Pressure application velocity was set to the maximum rate of 8.3 mmHg/msec.2, 3KCl, 2CaCl2, 10Hepes, 10Glucose  and intracellular solution (mM): 150KCl, 10EGTA, 10Hepes, 1EDTA . Electrodes were drawn from borosilicate patch glass (Sutter Instruments) and polished  to a resistance of 3–6 MOhms. Analog signals were filtered (1 kHz) using the built-in 4-pole Bessel filter of an Axopatch 200B patch clamp amplifier (Molecular Devices) in patch-mode and digitized at 20 kHz . The access resistance was monitored throughout the recordings to avoid incurring in excess series resistance, and care was put into keeping the series resistance low by either recording from cells with overall low levels of current (under 1nA) and using pipettes of small initial resistance.Whole-cell recordings were performed using extracellular solution (mM): 150NaCl, 2MgCl2, 2MgCl2, 10Hepes, 10Glucose . All recordings were done in excised outside-out mode. Analog signals were filtered (1 kHz) using the built-in 4-pole Bessel filter of an Axopatch 200B patch clamp amplifier (Molecular Devices) in patch- mode and digitized at 20 kHz .For single channel studies the following solutions were used (mM): Pipette: 150KCl, 10Hepes, 10EGTA . Bath: 150NaCl, 3KCl, 2CaCl2; 90CaCl2, 7.5Hepes, 7.5Glucose .For ion selectivity studies the following solutions were used (mM): Intracellular; 150KCl, 10Hepes, 10EGTA . Extracellular NaCl; 150NaCl, 10Hepes, 10Glucose . Extracellular NaGluconate; 152NaGluconate, 10Hepes, 10Glucose . Extracellular NMDG-Cl; 152NMDG-Cl, 10Hepes, 10Glucose . Extracellular CaClTotal RNA was extracted at days 0 (mouse embryonic stem cells), 2, 3, 4, 5, and 7 (motor neurons) of each differentiation using a Trizol/RNeasy hybrid protocol. Briefly, cells are homogeneized using a recommended volume of Trizol (Invitrogen), chloroform is added in the recommended volume and the mix is shaken vigorously. After centrifugation to allow phase separation, the aqueous phase is kept and mixed with 70% ethanol 1:1. The protocol follows using an RNeasy column (QIAGEN) and following the manufacture’s instructions. For days 5 and 7 a step was added previous RNA extraction: cells were sorted using a BDFACSAria Cell Sorter (BD) to isolate only the GFP-positive fraction, therefore enriching the sample in motor neurons. GFP-positive cells were sorted into Trizol LS (Invitrogen) and extraction of RNA proceeded as before.High throughput RNA sequencing was done in triplicates except for days 5 and 7, which were done in duplicate. Each duplicate or triplicate sample was obtained from an independent differentiation. The RNA samples were first treated with DNase, then one library per sample was prepared using Illumina’s TruSeq RNA Sample Prep Kit, where polyA-fragments were selected, followed by cDNA synthesis and ligation of amplification and sequencing adapters. Libraries were then individually barcoded and then pooled with six libraries per lane on an Illumina HiSeq 2500 instrument (Illumina). All samples were sequenced as single-read with read lengths of 50 bp. For analysis of RNA-seq data, reads were uploaded to the Galaxy environment  and were curated and trimmed according to the quality of the sequences using default options. Curated sequences were ran through Tophat for Illumina using a built- in reference genome mm10 (GRCm38/mm10) for mapping the reads to the mouse genome. Sequences were then ran through the Cufflinks package which assembles transcripts and estimates their abundances to obtain, for each sample, a list of transcripts with their associated transcript counts. Transcript counts are obtained as FPKMs (fragments per kilobase of transcript per million mapped reads). Finally, Cufflinks (CuffDiff) was used to calculate differential expression of transcripts between samples.High-throughput data is publicly available at the GEO database, for public access (accession number GSE106526).Piezo1 gene. hB9-GFP mES cells were then transfected with the px459 vector using Lipofectamine 2000 (Invitrogen) and selected with 1 µg/ml Puromycin for 2 day. After 1 day of recovery in Puromycin-free medium, transfected cells were dissociated and sparsely re-plated into 10 cm dishes. Single colonies were isolated after 7 days, expanded, and DNA was extracted using QuickExtract DNA Extraction solution (Epicentre). A 500 bp region containing the Cas9 target was amplified by PCR using the following primers: CGTGTGCATCCACGTATGA and AGGTGTGCACTGAAGGAACC. Obtained fragment was then sequenced. Sequencing results showed that some colonies contained a mix of 2 sequences, indicating differential mutations in both alleles of the Piezo1 gene. However, four colonies showed a clear single sequence, indicating a homozygous mutation near the PAM sequence. Two of those colonies were selected for electrophysiological studies. A third colony was added to the studies for figure 7.px459 (Addgene) was used to express Cas9 and guide RNA sequence along with a Puromycin resistance cassette according to published procedures . Two guiPiezo1 gene: TGCACTACTTCCACAGACCG, CAGGAAGATGAGCTTGGCGT, CTACTCCCTCTCACGTGTCCA, TCTACTGGCTGTTGCTGCC, CCAGCAACACAATGACCAGC, ATGGAGCCGCACGTGCTG, GATGCTGCCCCAGCCGTGGG, GGCCTGCCTCATCTGGACGG, AGCAGTTGGGCGACCTGGGC, TGCCCGCCCAGGCTGTGTGC, AGCCCAGCTCGTGCTGTGGG, CACGGTAGACGGGCTGACGC, CGGCGCTATGAGAACAAGCC, CGACCGTGCCCTCTACCTGC, GGAGTATACTAATGAGAAGC, AGG GACGCTGTGTCCCTACC, TACTGGATCTATGTGTGCGC, CATACCAGGTCACACAGGTC, TCCTCCTGATGCTCAAGCAGAGG, CTAGGTCCAGCAGCCGGTCAG, CTCACTCCATCATGTTCGAGG. PCRs were done using Phusion HF (NEB) or Pfu Ultra II (Agilent). For some difficult reactions 5% DMSO was added to the PCR reaction. The Piezo1 construct from N2A cells was obtained from the Patapoutian lab. For whole cell poking of both constructs transfected into HEK293 cells the following solutions were used (mM): 150KCl, 10Hepes, 10EGTA  and 150NaCl, 3KCl, 2CaCl2, 2MgCl2, 10Hepes, 10Glucose .Total RNA was extracted from mES cells using RNeasy kit (QIAGEN) and cDNA was made using Quantitect Reverse Kit (QIAGEN). The following primers were used in various combinations to obtain PCR fragments that cover the entire coding region of the mouse ESC proliferation was measured by seeding in 250 ESC per well in 96 well plates coated with 5 ug/ml laminin5,2,1 (biolamina). Wells were stained with markers for all nuclei  and dead cells  and whole wells were imaged and quantified for live cells on days 0, 1, 3 and 6 using ImageExpress and Metamorph. ‘Naïve’ (Inner cell mass-like) ESC were maintained in ‘2i + LIF medium’ and transitioned to ‘primed’ (epiblast-like stem cells) EpiSC by incubation for 48 hr with mouse embryonic fibroblast conditioned medium with 20% ES cell grade FCS (CM) containing activin (from feeders) and added bFGF  without LIF or 2i used for naïve culture, and germ layer differentiation was triggered by adding 50 ng/ml human recombinant BMP4 (R & D) to CM and incubating for 48 hr. Cultures for staining were seeded as above on Ibidi uclear eight well slides, or 28 kPa PDMs dishes (Ibidi), fixed with 4%PFA, permeabilized with 0.1%Triton, stained with the following primary antibodies  H3 1:500, #4178, Abcam; rabbit cleaved Caspase3 1:400, #9664S, Cell Signaling Technologies) and secondary antibodies  and DAPI (Life), imaged on a Leica SP8 inverted confocal with gallium arsenide detectors at 12 bits, 1024 × 1024 pixels using an HCX PL APO CS 20x/0.75NA air objective at 1 Airy unit pinhole and Nyquist spacings. Raw image data was analyzed quantitatively by unbiased automated image analysis, Metamorph MultiWavelength Cell Scoring module, and qualitatively by 3D blind deconvolution (Autoquant) 10 iterations and 3D-rendering , contrast and gain were adjusted to maximize visual legibility, but kept constant across all fields and lines from the same stain. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, including Kenton J Swartz as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Richard Aldrich as the Senior Editor.Thank you for submitting your article "Piezo1 forms a slowly-inactivating mechanosensory channel in mouse embryonic stem cells" for consideration by Summary:This is an interesting and well executed study showing that mouse embryonic stems cells express mechanosensitive ion channels that exhibit slowly desensitizing properties in response to poking with mechanically actuated probe. Measurements of whole-cell mechanosensitive currents with different cations in the extracellular solution suggest that the channels are relatively non-selective between cations, with a small preference for calcium over sodium or potassium. Single channel measurements with excised patches show similar kinetic properties when elicited with pressure-clamp and compared to whole-cell measurements obtained with the poking assay, and they show that the mechanosensitive channels have a single channel conductance of ~25 pS. When ES cells are differentiated into motor neurons the mechanosensitive currents become more rapidly desensitizing before they disappear, as voltage-gated conductances become larger. Interestingly, the authors show that expression of Piezo1 correlates with the amplitude of the mechanosensitive currents during differentiation, and KO of Piezo1 leads to loss of mechanosensitive currents. Finally, the authors clone Piezo1 from the ES cells and although they identify three residues differing from the previously cloned Piezo1 subunit, expression in mammalian cells gives rise to rapidly desensitizing currents that resemble those previously reported for the Piezo1 channel. The interesting take home message is that a regulatory mechanism must exist in ES cells that converts Piezo1 from rapidly desensitizing to slowly desensitizing. The manuscript was easy to read and comprehend and it makes a valuable contribution to the literature.eLife if the authors could provide evidence for what function Piezo1 might have in mES cells or for the mechanism by which extrinsic factors might be shaping Piezo1 kinetics in different cellular environments.Although all three reviewers were enthusiastic about this study, the consensus was that the work would be more appropriate for Essential revisions:1) Piezo1 has known to be widely expressed, so the observation they are in mES is interesting, but perhaps not particularly surprising. More to the point, both Piezo1 and Piezo2 channels have already been shown to have different kinetics depending on the cell types where they are found. Piezo2-dependent currents in Merkel cells have a shoulder current not commonly observed in sensory neurons . Very recently, it was shown that Piezo2 mediates at least some of the slower adapting currents in duck sensory neurons . Perhaps more to the point, the currents reported here look remarkably similar to those previously reported to be found in some types of HEK293 cells .2) While the authors discuss possible implications of Piezo1 function in mES cells (Discussion section), they do not attempt to test those hypotheses experimentally. This is puzzling given the authors took the time to create Piezo1 KO mES cells. There seems to be a missed opportunity to experimentally examine the role of mechanosensitive signaling in mES cells differentiation, outgrowth, survival etc. At a minimum, the authors could have tested their hypothesis about a role for Piezo1 in sensing substrate stiffness.3) The authors do a nice job of showing that the mES mechanosensitive currents are mediated by Piezo1  and that the kinetics change over the course of experimental differentiation into motor neuron-like cells . Furthermore, they provide evidence that channels cloned for mES display faster kinetics when heterologously expressed in HEK293 . These observations provide a strong foundation, but the work would have considerably more impact if the authors could provide more mechanistic information about how these two cellular environments alter the kinetics of desensitization. Summary:This is an interesting and well executed study showing that mouse embryonic stems cells express mechanosensitive ion channels that exhibit slowly desensitizing properties in response to poking with mechanically actuated probe. Measurements of whole-cell mechanosensitive currents with different cations in the extracellular solution suggest that the channels are relatively non-selective between cations, with a small preference for calcium over sodium or potassium. Single channel measurements with excised patches show similar kinetic properties when elicited with pressure-clamp and compared to whole-cell measurements obtained with the poking assay, and they show that the mechanosensitive channels have a single channel conductance of ~25 pS. When ES cells are differentiated into motor neurons the mechanosensitive currents become more rapidly desensitizing before they disappear, as voltage-gated conductances become larger. Interestingly, the authors show that expression of Piezo1 correlates with the amplitude of the mechanosensitive currents during differentiation, and KO of Piezo1 leads to loss of mechanosensitive currents. Finally, the authors clone Piezo1 from the ES cells and although they identify three residues differing from the previously cloned Piezo1 subunit, expression in mammalian cells gives rise to rapidly desensitizing currents that resemble those previously reported for the Piezo1 channel. The interesting take home message is that a regulatory mechanism must exist in ES cells that converts Piezo1 from rapidly desensitizing to slowly desensitizing. The manuscript was easy to read and comprehend and it makes a valuable contribution to the literature.Although all three reviewers were enthusiastic about this study, the consensus was that the work would be more appropriate for eLife if the authors could provide evidence for what function Piezo1 might have in mES cells or for the mechanism by which extrinsic factors might be shaping Piezo1 kinetics in different cellular environments.We thank the reviews for their helpful comments on our manuscript. We have addressed all of the points by either modifying the text, adding experiments, or commenting on the issue.A major point brought up by the reviewers concerned the lack of a functional model that makes sense of the expression of Piezo1 in stem cells. To address this issue, we attempted several lines of experiments aimed to address what the potential role of Piezo1 in stem cells is. Unfortunately, we were unable to find a direct effect of Piezo1 expression in several quantitative and qualitative measures of stem cell differentiation. However, we did note a proliferation defect in Piezo1 knockout cells, indicating that expression of Piezo1 could be involved in setting the normal division rate of cells. We must point out that while our efforts tried to span a broad set of conditions, there is as of yet no clear model for the role of mechanosensory processes in early stem cells, and therefore it is possible that the role of Piezo1 could be involved in untested conditions.Another major point concerned the lack of model explaining how the Piezo1 channel changes its kinetics in different cellular contexts. We believe that, although of major interest, it escapes the scope of our current work. Below we address the reviewer’s comments in detail.Essential revisions:1) Piezo1 has known to be widely expressed, so the observation they are in mES is interesting, but perhaps not particularly surprising. More to the point, both Piezo1 and Piezo2 channels have already been shown to have different kinetics depending on the cell types where they are found. Piezo2-dependent currents in Merkel cells have a shoulder current not commonly observed in sensory neurons . Very recently it was shown that Piezo2 mediates at least some of the slower adapting currents in duck sensory neurons . Perhaps more to the point, the currents reported here look remarkably similar to those previously reported to be found in some types of HEK293 cells .Thank you for the comment, we have added the recommended references to broaden our cited sources. Conceptually, indeed, Piezo1 has been shown to be expressed in several cell types, and its kinetics have been shown to be modestly variable. For example, in Schneider et al. (2017), the authors report a shift in inactivation constant from 3.1 ± 0.17 ms in mouse Piezo2 to 5.1 ± 0.47 ms in duck Piezo2. The other reports do not measure inactivation constants but from the figures they appear to be in the same range. Though these reports obviously bear great significance, to our knowledge, no paper has reported such dramatically slowed kinetics – turning the channel at times into a non-inactivating channel – for Piezo1 as we can unequivocally attribute exclusively to Piezo1 in stem cells. In addition, we believe that the discovery of a specific developmental program that drastically modifies the desensitizing behavior of Piezo suggests the relevance of the regulation of Piezo kinetics as an unexplored novel regulatory mechanism. Finally, although the Piezo1 gene has been shown to be widely expressed, as the reviewer rightly points out, the level of current that we found in mES cells is many times greater in magnitude larger than those observed in other non-sensory types such as HEK293 cells. This is interesting, given that mouse embryonic stem cells are the most ‘stem’ state of mammalian cells, that can give rise to any other cell type and whose development program is still widely undescribed. The potential effect of mechanosensory components in the development of embryos is as of yet understudied.2) While the authors discuss possible implications of Piezo1 function in mES cells (Discussion section), they do not attempt to test those hypotheses experimentally. This is puzzling given the authors took the time to create Piezo1 KO mES cells. There seems to be a missed opportunity to experimentally examine the role of mechanosensitive signaling in mES cells differentiation, outgrowth, survival etc. At a minimum, the authors could have tested their hypothesis about a role for Piezo1 in sensing substrate stiffness.We appreciate the encouragement to pursue these experiments, and in response have done extensive additional research. The new data has been added as Figure 7 and Table 1, and the resulting conclusions are now incorporated in the relevant sections. As a summary, we compared Piezo1 knockout to wild type mES cells at pluripotency and during early differentiation. Using both qualitative and quantitative measures we found a proliferation defect in the Piezo1 knock out mES cells, but no difference between both phenotypes in any other parameter. We can attribute the proliferation defect to cell cycle interphase lengthening, but we were not able to link it to any mechanosensory process. As suggested by the reviewer, our experiments also included testing mES response to differential substrate stiffness, however Piezo1 genotype did not affect this response to the tested substrates. While we were unable to find a specific role for Piezo1 in mES cells, it is also unclear what the overall role of mechanosensory processes in stem cell differentiation is, and therefore it is possible that we have not tested the appropriate parameters, as it is unknown which assay would be the appropriate one.3) The authors do a nice job of showing that the mES mechanosensitive currents are mediated by Piezo1  and that the kinetics change over the course of experimental differentiation into motor neuron-like cells . Furthermore, they provide evidence that channels cloned for mES display faster kinetics when heterologously expressed in HEK293 . These observations provide a strong foundation, but the work would have considerably more impact if the authors could provide more mechanistic information about how these two cellular environments alter the kinetics of desensitization.We kindly thank the reviewers for their overall positive comments. We agree with the observation that a more impactful result would derive from studying the contribution of cellular environment to channel function, however, we think that the initial observation and careful testing reported in this work stands on its own to contribute to the increasingly complex field of mechanosensory ion channels.