Mechanosensitive PIEZO ion channels are evolutionarily conserved proteins whose presence is critical for normal physiology in multicellular organisms. Here we show that, in addition to mechanical stimuli, PIEZO channels are also powerfully modulated by voltage and can even switch to a purely voltage-gated mode. Mutations that cause human diseases, such as xerocytosis, profoundly shift voltage sensitivity of PIEZO1 channels toward the resting membrane potential and strongly promote voltage gating. Voltage modulation may be explained by the presence of an inactivation gate in the pore, the opening of which is promoted by outward permeation. Older invertebrate (fly) and vertebrate (fish) PIEZO proteins are also voltage sensitive, but voltage gating is a much more prominent feature of these older channels. We propose that the voltage sensitivity of PIEZO channels is a deep property co-opted to add a regulatory mechanism for PIEZO activation in widely different cellular contexts. PIEZO proteins form mechanosensitive ion channels. Here the authors present electrophysiological measurements that show that PIEZO channels are also modulated by voltage and can switch to a purely voltage gated mode, which is an evolutionary conserved property of this channel family. The PIEZO2 protein is found in sensory neurons of the dorsal root ganglia and Merkel cells where its presence is essential for mechanotransduction6. Mice without Piezo2 in sensory neurons lack normal touch sensation and proprioception, and severe loss of function alleles in humans are also associated with loss of proprioception and touch sensation9. Genetic ablation of either the Piezo1 or Piezo2 genes in mice leads to either embryonic or early post-natal lethality10. Recently, both mouse and human genetics have revealed roles for PIEZO-mechanosensing ion channels in a variety of non-sensory cellular physiology ranging from cartilage formation by chondrocytes12, epithelial sheet homeostasis14, growth cone guidance15, arterial smooth muscle remodeling16 to blood cell shape regulation17.The mechanically gated ion channels PIEZO1 and PIEZO2 are involved in a variety of physiological functions essential to life. PIEZO1 plays a fundamental role in the development of the mouse vasculature as well as lymphatic systems20. High resolution structures of the mouse PIEZO1 protein were recently obtained revealing a trimeric three-bladed, propeller-shaped structure with a central pore-forming module comprising of an outer helix (OH), C-terminal extracellular domain (CED), inner helix (IH), and intracellular C-terminal domain (CTD)23. The peripheral regions of PIEZO1 are composed of the extracellular “blade” domains, 36 peripheral helices (PHs) in each subunit and intracellular “beam” and “anchor” domains23. The PIEZO1 structure has facilitated biophysical exploration of the ion-channel pore28, and chimeric structures suggest that the N-terminal non-pore containing region confers mechanosensitivity on the channel28. However, recent data suggested that these models need further validation29.The mouse PIEZO1 protein forms a pore-forming ion channel directly gated by membrane stretch31. However, the role of membrane voltage in modulating PIEZO channel activity has barely been addressed despite the fact that both mammalian stretch-activated potassium channels36, as well as bacterial stretch-activated channels are voltage sensitive37. Here, we asked whether voltage can modulate or even gate vertebrate and invertebrate PIEZO channels. We show that both PIEZO1 and PIEZO2 show significant voltage sensitivity that is dependent on critical residues in the pore-lining region of the channel. We provide evidence for an inactivation gate that closes following inward permeation which under physiological conditions renders >90% of the channels unavailable mechanical gating. Outward permeation of the channel is sufficient to initiate a slow conformational change that opens the inactivation gate. Pathological human mutations in Piezo1 primarily weaken the inactivation gate and render the channels less sensitive to voltage modulation. The same mutations also allow PIEZO1 to behave as a voltage-gated ion channel in the absence of mechanical stimuli. Finally, we show that the biophysical properties of both invertebrate (Drosophila melanogaster) and other vertebrate (Danio rerio) PIEZOs are much more reminiscent of classical voltage-gated channels than mammalian PIEZOs.Proteins like STOML3 have been identified that can dramatically increase the sensitivity of PIEZO channels to mechanical force28. We subjected excised outside-out patches from the N2a cells of the overexpressing mouse PIEZO1 to an I/V protocol from −100 to +100 mV in symmetrical Na+, without divalent cations, while stimulating the patch with a saturating pressure pulse. However, at more positive voltages the I/V relationship showed strong outward rectification   Fig. . Single nce Fig. .Fig. 1ReIins-60 mV/I60 mV) was 1.13 ± 0.06 (n = 8) . We have observed a high variation in saturation levels of Boltzmann fits depending on the patch. While some patches saturated at 140 mV, others did not. Higher voltages might achieve consistent saturation levels, but were not achievable due to frequent patch rupture. Examination of the Boltzmann fit indicates that at physiological resting membrane potentials (<0 mV), the apparent open probability, or PIEZO1 channel availability was <10% of the maximum made available by a depolarizing pre-pulse . Upon reaching steady-state activation, the voltage was stepped to −60 mV and the peak instantaneous currents were measured. The rectification index ( 8) Fig. , suggest 8) Fig. . Upon re 8) Fig.  establislse Fig. .31, and here we also measured fast inactivation time constants . It has been reported that repetitive mechanical stimulation can drive PIEZO1 channels into an irreversible non-inactivating and desensitized state39. The desensitized state, induced by repetitive stimulation (every 1 s), is characterized by a loss of inactivation as reflected in a reduction in the ratio of peak to steady-state current . This experiment demonstrates how voltage or outward permeation can reset the channel to a fully active state. To address whether permeation or positive voltage were necessary to reset desensitization, we repeated the experiments as above but did not apply pressure pulse P4 while holding the patch at +40 mV. Under these conditions, no outward current was measured and PIEZO1 channels did not recover from desensitization; the P5/P1 was decreased to 0.25 ± 0.05 (n = 13)  Fig. .+ concentration  and measured the Erev of +43 ± 1 mV (five cells) with a ramp protocol   Fig. . These eWe noticed that the transition between the desensitized state  during the second pressure step, and measured the changes in amplitude and rise time of the last step at +60 mV . Thus, the inactivation state of PIEZO1 was reversible and the transition occurs in a manner proportional to the amount of permeating ions. There is thus a mechanistic link between permeation and inactivation which implies the presence of an inactivation gate along the permeation path. The opening of an inactivation gate would depend on the outward flow of ions through the pore. Furthermore, this inactivation gate can be forced open by increasing the outward driving force during permeation, thus establishing an essential role for permeating ions in the gating of PIEZO1 . We found that larger outward currents measured in the conditioning step were followed by larger inward currents measured at −60 mV Fig. . By plotZO1 Fig. .Fig. 3Inn = 12 without conditioning step, black trace, and 68.3 ± 3.7 mV n = 5, with conditioning step, red trace, Student’s t-test p = 0.0036, dF = 15). Thus, outward permeation increases the apparent open probability of the channels. The shift in I/Imax relation induced by a positive pre-pulse effectively leads to a threefold increase in the number of available channels at physiological membrane potentials (<0 mV) from 5 to 15% , a residue located at the base of the pore-forming IH in the CTD of mPIEZO128. The human R2456H mutation has a strong inactivation phenotype46, which we confirmed for the mouse PIEZO1 R2482H mutant  . We introduced further xerocytosis mutations into the mouse cDNA: R1353P (human R1358P17) is located on the beam structure and may interact with the CTD23, A2036T (human A2020T17) is located on a peripheral membrane helix that is resolved in the structure, and T2143M (human T2127M) is located in the middle of the anchor domain  is predicted to be located about 17 Å distant from arginine (2482) that is located on the adjacent subunit. Thus, both residues R2482 and T2143 could participate in a spatially restricted domain that controls voltage-dependent gating of PIEZO1 channels.We measured the apparent open probability with tail current protocols and observed a 50 mV leftward shift in the current–voltage relationship for the R2482H mutant compared to its wild type. When R2482 was mutated to lysine (K)st) Fig. . The neust) Fig. , suggestain Fig. . In contain Fig. . However47. Mechanically activated PIEZO2 currents inactivate faster than PIEZO1 currents31. We hypothesized that the apparent open probability of PIEZO2 channels are also modulated by voltage. However, we were unable to record the stretch-activated currents in excised or cell-attached patches from cells overexpressing PIEZO2  and the reverse PIEZO2/PIEZO1  by fusing the N-terminal sequence of the first protein and including the so-called anchor region with the remaining downstream sequences of the second protein. The C-terminal sequence of the chimeras included: the last two transmembrane-spanning domains that putatively form the channel pore, the so-called IH and OH, the CED, and CTD ; 37.6 ± 4.6 mmHg (10 cells) and 42.4 ± 4.7 mmHg, respectively . These data show that the pore module of PIEZO2 in combination with the N-terminal region of PIEZO1 is also capable of sensing changes in voltage. However, the unexpected kinetics of the P2/P1 chimeric channel limits conclusions about the contribution of the PIEZO2 N-terminus to voltage modulation.The chimeric P1/P2 channel also produced robust tail currents at −60 mV Fig.  the ampl5). However, the R2482H and R2482K mutant channels showed an unexpected additional feature: current deactivation was seen immediately after the pulse, but 20–40 ms later the current started to reactivate with a sag phase and increased or maintained outward current  and 19.5 ± 4.5 mV (5 cells R2482K), respectively , produced no appreciable channel opening when Yoda1 was applied either in the extracellular buffer or via the recording pipette . We then performed a voltage protocol in absence of pressure and we observed robust voltage-activated outward currents with V50 of 31.9 ± 7.4 mV (5 cells). The speed of current activation increased exponentially with voltage  was found to be crucial for epithelial homeostasis14. Here, we cloned cDNAs encoding the Drosophila , Zebrafish Piezo1 (DrPIEZO1), and the human PIEZO1 (hPIEZO1) in order to compare the voltage-dependent behavior of PIEZO channels across three orders of the animal kingdom. To study the orthologues under the same controlled experiments, we used the N2aPiezo1−/− cells , which is typical for several PIEZO1 channels  and a slope of 7.9 ± 1.3 with a corresponding gating charge e0 of 3.8 ± 0.7. The DmPIEZO protein was also opened by positive voltage pulses, but showed markedly slower activation kinetics and voltages as high as 140 mV still did not produce saturating activation  also desensitized quickly in response to consecutive pressure stimuli Fig. . In contion Fig. . Consequ49. Our data can be explained by the existence of an inactivation gate, for which a closed conformation is strongly favored at physiological resting membrane potentials. Opening of the inactivation gate is promoted by outward permeation, and in this conformation voltage gating of the channel is possible   Fig. . Althoug52 and this could take place via regulation of PIEZO channels53. It is thus conceivable that inflammatory signals could shift voltage sensitivity of the PIEZO channels into a range where action potential firing in the presence of mechanical force could release many more channels for activation.By using conditioning positive voltage steps, we found that it requires considerable driving force to open the inactivation gate greater than +80 mV to activate all channels Fig. . Neverth31. PIEZO1 channel activity has also been extensively studied in excised patches and in artificial lipid bilayers where, similarly to TRAAK channels54, membrane stretch or increased curvature are sufficient to gate the channel20. So far the evidence that PIEZO2 channels can be gated by membrane stretch has been lacking. Furthermore, attempts to elicit pressure-mediated currents in outside-out patches from cells overexpressing PIEZO2 failed both in the heterologous system (this report) and in Merkel cells, where PIEZO2 is abundantly expressed48. We show using PIEZO1/PIEZO2 chimeras that the N-terminal region of PIEZO1 allowed us to measure pressure activated currents in excised patches from N2a cells, in which a large portion of Piezo1 gene had been deleted . It seems reasonable to conclude that stretch sensing domains reside within the N-terminal region of both PIEZO proteins. However during evolution, PIEZO2 might have lost the ability to transfer mechanical forces derived from membrane stretch to open the pore. By joining PIEZO2 N-terminal sequences to the pore module of PIEZO1, this lost transduction pathway appeared to be reconstituted although with altered inactivation kinetics. Alternatively, the “stretch sensor” of PIEZO1 does not reside in one region of the protein, but is dispersed across distant domains like the “blades” and the pore module21. Thus both modules might act together to sense changes in tension in the surrounding lipid bilayer.Despite the high amino acid sequence homology between PIEZO1 and PIEZO2, these two channels appear to be activated by different kinds of mechanical stimuli. The whole-cell patch-clamp experiments in cells have provided evidence that expression of PIEZO1 or PIEZO2 is accompanied by a fast current activated by cell indentation or substrate deflection57. Our data thus suggest that in erythrocytes the percentage of PIEZO1 channels available for activation could change from 5% in normal individuals to more than 40% in individuals carrying a single-point mutation  might confer voltage-modulation. It is worth noting in this context that arginine residues in the S1–S4 domains play a fundamental role in voltage sensing in most canonical voltage-gated ion channels61. Interestingly, voltage-modulation of pressure-gated ion channels has previously been described for the archetypical pressure sensitive bacterial channel MscS, which also requires arginine residue within the lipid bilayer62. However, so far there are no reports that bacterial mechanosensitive channels can be directly voltage gated.The mutated 2482 arginine residue is located at the bottom of the IH of PIEZO1, a position close to the inner pore. Interestingly, in other ion-channels families, arginine residues at the extremities of pore-lining regions have been shown to be essential for anchoring the helices to the lipid bilayer and to stabilize the closed conformation of the channelOur data show that PIEZO1 is a polymodal channel that can be gated by voltage following a mechanical stimulus. A mutant channel involved in human disease (mouse R2482H/K) undergoes an unprecedented switch from a pressure-gated to a voltage-gated mode at voltages more positive than ~30 mV. The transition is caused by a sustained outward-ion flux in the absence of pressure. Although outside-out patches are constantly subject to a tension within the recording pipette, such tension is not sufficient to open even sensitive channels as the R2482K mutant nor PIEZO1 wt sensitized by Yoda1 , as to sense voltage, charged residues position within the electric field change upon voltage sensor activation. We estimated the gating charges from the slope of macroscopic currents to provide a lower limit of the charge movement. However, we observed a threefold increase in e0 upon switching from pressure to voltage-gating mode  were cultured in DMEM/Opti-MEM (50/50) containing 5% fetal calf serum and 1% penicillin and streptomycin according to the provider’s protocol (Neuro-2a ATCC CCL-131). The medium was changed to a serum-free medium before transfection. Cells were transfected with Piezo1 (a gift from Dr. Ardem Patapoutian) or chimeric Piezo1–Piezo2 cDNA constructs containing an IRES-EGFP sequence to select transfected cells. Cells were transfected in a 35 mm petri dish, pre-coated with poly-(l)-lysine, with 1 μg DNA and 3 μl of HD Fugene (Promega) following the manufacturer’s protocol and were recorded 12–48 h after transfection. Only EGFP expressing cells were selected for electrophysiological recordings.N2a cells (wt and N2a Mutations were introduced in the mouse Piezo1 plasmid using the XL QuikChange™ Site Directed Mutagenesis (Agilent Technologies). The chimera between Piezo1 and Piezo2 was produced by PCR by joining the residues 1-2188 of mPiezo1 and 2472-2822 of mPiezo2. The resulting chimeric construct of 2539 amino acids was cloned into an IRES-EGFP containing vector by SLIC reaction (primers supplied in Supplementary Table D. melanogaster Piezo was cloned from Drosophila mRNA (a gift from Dr. Robert Zinzen), while the D. rerio (zebrafish) Piezo1 was cloned from pooled individuals at 48 h post fertilization (a gift from Dr. Daniela Panakova). Both cDNA were cloned into an IRES-EGFP vector and transfected into N2a Piezo1−/− cells. Only EGFP expressing cells were selected for electrophysiological recordings.The Piezo1 gene was generated using CRISPR/Cas9 technology. Four gRNAs targeting exon 6 and exon 45 were generated using the gRNA designer (http://crispr.mit.edu/) for the nickase Cas9 . N2a cells were transfected with gRNA and Cas9n and single cell sorted 1 week after transfection to generate a clonal Piezo1−/− cell line. The selected clone had three copies  of Piezo1, a deletion of at least 17 Kb in each allele. More importantly, no mechanically activated currents were detected by using soma indentation . Soma indentation experiments were performed in whole-cell configuration using microelectrodes with a resistance between 2 and 4 MΩ. Uncompensated series resistance values were less than 2 MΩ. Cells were held at −60 mV and mechanical stimulation was performed using a blunt glass probe (tip size 3–4 μm).2. Extracellular solution (in millimolar): 140 NaCl, ten Hepes, five glucose, one MgCl2, and two CaCl2.Experiments in outside-out configurations were performed in symmetrical ionic conditions and in a divalent-free buffer. Solutions contained (in millimolar): 140 NaCl, 10 HEPES, 5 mM EGTA adjusted to pH 7.4 with the NaOH. Whole-cell experiments were performed with the following solutions intracellularly (in millimolar): 140 KCl, ten Hepes, five EGTA, and one MgClFor experiments where the intracellular concentrations of NaCl were altered, sucrose was used as a replacement. In Fig. γ is the slope of the line, I is the single current measured, V is the voltage, and C is the reversal potential . Ten to ninety percent rise times were calculated using an in-built calculation of Patchmaster. The baseline and the peak were first detected. Successively, the time that it takes for the current to go from 10% to 90% of the peak value was calculated.Currents recorded in outside out and whole cell were sampled at 10 kHz and filtered at 3 kHz using an EPC-10 amplifier and Patchmaster software . The currents were subsequently analyzed using FitMaster . To calculate the single channel conductance of PIEZO1, 5–20 s long segments containing single channel openings were first filtered at 1 kHz. Subsequently, all point histograms were constructed using FitMaster. From a double Gaussian fit, the single channel conductance was calculated by plotting the average current at each potential versus the voltage. Slope conductance values at positive and negative holding potentials were obtained by plotting current–voltage relationships and by fitting the following relationship to the data points (each point was the average of 50–200 openings). RT/ZF . Individual fit from single cells were pooled together and values are expressed as mean ± SEM.Tail currents were measured at −60 mV, unless otherwise stated. Peak currents at −60 mV were leak subtracted during the analysis, normalized to the largest current and fitted to a standard Boltzmann equation:We refer to desensitization of the process that involves repetitive stimuli that lead ultimately to a decrease in channel amplitude throughout the course of the experiment. We refer to inactivation to the altered conducting state that PIEZO1 undergoes during a mechanical stimulation. This becomes apparent through the alteration of the time course of the decay of pressure-mediated currents.t-test, paired or unpaired depending on the experimental setup. Non-parametric datasets were compared using a Mann–Whitney test. One-way ANOVA and Dunnett’s post-hoc test were used as indicated in the figure legends. Data are reported as mean ± SEM.Parametric datasets were compared using a two-tailed, Student’s Other data are available from the corresponding authors upon reasonable request.Supplementary InformationPeer Review File


Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% − 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells. Despite its potential, scRNA-seq data are often noisy, which are caused by a combination of experimental factors, such as the limited efficiency in RNA capture from single cells, and also by analytical factors, such as the challenges in separating true variation from technical noise7. The quality of scRNA-seq data depends on mRNA capture efficiency8, the protocol utilised to obtain libraries, as well as sequence coverage and length4. Bioinformatics tools for the analyses of scRNA-seq data have been rapidly evolving, whereby various algorithms have been proposed to resolve the issues related to scRNA-seq compared to classical bulk transcriptomic analysis11. However, the lack of a consensus in the data analyses further contributes to difficulties in assessing the quality of the data analysed so far.Single cell RNA sequencing (scRNA-seq) has vastly improved our ability to determine gene expression and transcript isoform diversity at a genome-wide scale in different populations of cells. scRNA-seq is becoming a powerful technology for the analysis of heterogeneous immune cells subsetsi.e., the expected number of reads per cell) and read length6. These are two important experimental parameters that can be controlled, and which need to be often predetermined before sequencing. For bulk RNA-seq data, sequencing depth and read length are known to affect the quality of the analysis12. For scRNA-seq it has been shown that half a million reads per cell are sufficient to detect most of the genes expressed, and that one million reads are sufficient to estimate the mean and variance of gene expression13. Low coverage scRNA-seq has also been utilised to show that 50,000 reads per cell are sufficient to classify a cell type in a sample of 301 cells14. Nevertheless, this may not be sufficient when more homogenous populations are involved, for example T cell subsets, such as central memory and effector memory cells. In these scenarios, deep sequencing of single cell library may be required for improving detection of genes with low expression6. Indeed, an important issue for scRNA-seq data is the very large number of genes with no detectable expression in a cell6. This overrepresentation of zeros in scRNA-seq datasets makes it difficult to distinguish technical dropout of transcripts from true biological variation between cells3 and statistical methods have been developed to at least control this issue (e.g.15).One important consideration in designing scRNA-seq experiments is to decide on the desired sequencing depth , which identify the specific recognition of the cognate antigen. TCRs are heterodimer proteins composed of two chains, α and β, and a subset of those expressing the γδ chains, which result from genetic recombination of the V(D)J genes. The diversity of TCRαβ repertoire has been associated with successful control of many pathogens17, and more recently with outcome of checkpoint inhibitor immunotherapy for patients with metastatic melanoma18. The third complementarity-determining region (CDR3) of the TCR α and β chains forms loops that engage amino acid residues of peptides in complex with MHC. Detection of the CDR3 region is a crucial step to accurately identify the clonality of a T cell repertoire, for instance responding to a viral infection. The highly polymorphic nature of the TCR genes has made their identification very difficult in bulk population sequencing datasets. In the last decade, deep sequencing approaches of bulk TCRs focussed on either α or β chains19. The advent of scRNA-seq allowed the identification of the full length TCR of both α and β chains (referred to hereafter as TCRαβ) from T cells21. This has now led to the capacity to simultaneously detect TCRαβ and full gene expression profiles in one experiment, thereby allowing direct study of TCR diversity and its interaction with the T cell functions reflected in gene expression profiles.To answer these questions, we have focussed on assessing the quality of available scRNA-seq data from T cells, which form a highly heterogeneous population of lymphocytes that play a vital role in mounting successful adaptive immune responses against intracellular pathogens and tumoursIn this study we performed a comprehensive analysis of the impact of sequencing depth and read length on the detection of full length TCRαβ sequences, as well as estimation of gene expression and its effect on cell-type identification. Our study aims to fill this gap through performing a re-analysis of eight published scRNA-seq data that have a wide range of read length and sequencing depth, and analysis of simulated datasets that were subsampled from a deeply sequenced human T-cell scRNA-seq dataset. The analysis suggests important precautionary steps for researchers seeking to maximise throughput of single cell experiments without compromising the quality of the results.22 and ArrayExpress23 to identify relevant T-cell scRNA-seq data published prior to April 2016. Eight datasets were identified with accessible data, collectively profiling 1,305 single cells  reads per cell) and read length (25–215 bp)   Table . Six of %) Table . In term%) Table .Table 2T28.To further assess the quality of the reconstruction of TCRαβ sequence, we analysed the distribution of CDR3 amino acid sequences across both α and β chains, and the distribution of single cells carrying double α chains. The average CDR3 length of the reconstructed TCRαβ sequences with VDJPuzzle was 14 amino acids for both α and β chains Fig. , with siOne of the major advantages of using scRNA-seq to reconstruct TCR sequences is the possibility to detect double α chains within a single T cell. Overall, 30% (n = 395) of the cells analysed here presented more than one α but not double β. In a single study . From each of the original single cell data (n = 54), we generated 16 randomly subsampled scRNA-seq datasets with all combinations of four different sequencing depths  and four different read lengths   were considered as an exact TCRαβ reconstruction.To systematically investigate the effect of sequencing depth and read length, we generated simulated datasets with different sequencing depth and read length to assess the success rate of TCRαβ reconstruction. Simulated datasets were all derived from the original datasets 1, which had deep coverage (~8.4 million PE reads per cell), and long read length (150 bp) (Table bp) Fig. . For eacted Figs  and S3. r = 0.97, p < 0.01).Success rate of paired α and β was above 80% for datasets which had a minimum read length of 50 bp and a depth of at least 0.25 million reads. This rate was substantially diminished up to 0% for datasets with a number of PE reads per cell below 0.25 million PE reads Fig. . FinallyNext, we used the 16 subsampled scRNA-seq datasets to investigate the effect of sequencing depth and read length on read alignment and gene expression quantification. Surprisingly, we observed a slight increase in the total number of aligned PE reads in datasets with shorter read length, especially when the read length was below 100 bp Fig. . This hiTo assess the effect of this trend on the quantification of genes, fragments per kilo base per million (FPKM) were calculated allowing only one alignment per read, hence eliminating a potential confounding factor of multiple alignments. We found that the number of detectable expressed genes (those with FPKM >1) was positively correlated with sequencing depth (Pearson correlation = 0.89) but negatively correlated with read length (Pearson correlation = −0.93). The number of genes that were expressed in at least 10% of the cells showed a similar correlation with sequencing depth and read length Table . NotablyIn order to quantify the reliability of the gene expression profile as a function of read length and sequencing depth, two simulated datasets with a sequencing depth of 0.05 million PE reads were generated, with read length of 25 bp and 150 bp, respectively. Two replicates for each dataset were simulated. This analysis showed a significantly higher correlation between the gene expression profiles of paired cells from the two replicates with read length 150 bp when compared to the two replicates with read length 25 bp Fig. . This re20, a clustering algorithm was applied on all the simulated datasets. A newly developed bioinformatics tool CIDR30 was used to perform dimensionality reduction, Principal Coordinates Analysis (PCoA) and hierarchical clustering on the scRNA-seq gene expression profiles. When cutting the hierarchical clustering to form three clusters based on the experimentally validated cell subsets in the original data , CIDR achieved the tightest clustering when the dataset has > = 100 bp long PE reads , two genes constitutively expressed in CD8+ T cells (CD8B and TRAC), and one transcription factor . The analysis showed that, contrary to the expectation, the gene expression profile of the selected housekeeping genes varied significantly for low depth and short reads ) was analysed for highly expressed genes (average FPKM >100), lowly expressed genes (average FPKM <100), housekeeping genes, and transcription factors in all the subsampled simulated datasets. Independent of the gene category, there was a reduction in the number of genes identified with an expression level below 100 FPKM in datasets with a low sequencing depth  is associated with a higher number of detected genes when compared to datasets with longer reads. This increase in gene expression quantification is also associated to a diminished accuracy and increased misclassification of cell populations. Hence, short read datasets are more prone to technical noise. Future experimental designs should consider the quality of the reads as an important feature to obtain reliable results. Analyses of simulated and real scRNA-seq datasets showed that current methods, such as Smart-seq2 are consistent with a capture efficiency between 3–10% of the total mRNA available8. Indeed, the effect of low sequencing depth in the quality of gene expression quantification and TCR reconstruction is likely to be associated to the poor library capture efficiency of mRNA from single cells (<10%)8, hence it is conceivable that downstream analyses are not affected by large increase in sequencing depth. This study has focussed on T cells, however the results provided here are likely to be valid for other cell types. Notably, in this study we analysed resting memory T cells20, which are likely to be affected by limited mRNA available compared to other more active cell types such as effector cells. Previous studies have shown that the technical noise strongly depends on the mRNA content of the cell, which is a limiting factor in the detection of biological variation33. It is therefore likely that these results may be relevant for other cell types with a resting state, such as naïve cells, quiescent cells and dormant cancer cells.This study explored how sequencing depth and read length of scRNA-seq dataset affect various downstream analyses, such as transcript reconstruction, gene expression estimation and cell-type identification. The overall messages of this study can be summarised with two major findings. Firstly, by combining available algorithms for TCRαβ detection, along with simulation-based analysis, this study revealed that accurate detection of full-length TCRαβ is possible and achievable with sequencing depth below 0.25 million PE reads, and with a minimum read length of 50 bp. The detection rate of full length TCRαβ is at least 80% for reads with a sequencing depth >0.25 million PE reads of length at least 50 bp. Notably, the success rate in TCR reconstruction was dramatically reduced for short read length datasets (25 bp). This result can be explained by the poor alignment quality of short reads across the highly variable region of the CDR3 genes. Both methods implemented for TCR reconstruction rely on a 6. This observation results from real zero expression genes that a single cell may have at the time of RNA extraction, as well as dropout events, which are due to inefficient mRNA capture and library processing.Here we have showed that clustering analysis with scRNA-seq data characterised by 0.25 million PE reads and length >50 bp can accurately distinguish three rare and relatively homogenous cell subsets of antigen specific T cells, thus suggesting that despite technical limitations current scRNA-seq data can successfully be applied to identify differences between rare T cell subsets, such as effector and memory subtypes during an immune response against a viral infection. On the other hand, this may not be sufficient when more homogenous populations are involved, such as central memory and effector memory T cells from the same antigen specific repertoire. Deep sequencing of single cell library may still be required to improve detection of low abundant transcripts. Indeed, an important issue for scRNA-seq data is the very large amount of genes with zero expression34. These approaches however still lacks the incorporation of full-length transcriptome sequencing, hence affecting the accurate detection of full length TCRαβ. In conclusion, this study showed that future analyses should consider the quality of sequencing output to ensure reliable and accurate single cell transcriptomic profiling.Full length TCRαβ can be accurately estimated and linked to the gene expression profile of the same cell. The analysis also showed multiple instances of single cells with at least two α and two β sequences detected. These findings are likely explained by the presence of multiple cells per well being sequenced, and the higher detection rate of double chains in the Th17 dataset (datasets 3 and 4) is likely due to the larger sample size compared to the other studies. The high success rate obtained with both available software programs further support the high quality of the scRNA-seq data, which significantly improve the quality of TCR reconstruction with more classical approaches such as bulk sequences and Sanger sequencing. Along with TCRαβ full-length data, the entire transcriptome can be interrogated to identify specific gene profiles associated to T cell subsets, along with the relationship with the TCRαβ clonotypes. Single cell approaches are therefore likely to increase further the accurate identification of novel markers, which could be utilised for detecting novel subpopulations of cells, for instance using flow cytometry. Another improvement is to introduce bar coding of the cell, with approaches such as MARS-seq35. The analysis tested the sensitivity of UMI and Smart-seq methods on the same samples by assessing the number of genes detected as a function of sequencing depth. This analysis showed that Smart-seq. 2 had the highest sensitivity of detection, and 0.625 Million PE reads were sufficient to obtain an optimum number of genes, which is in line with our simulations. UMI-methods however quantified mRNA levels with less amplification noise due to the use of UMI. A comprehensive analysis of 15 experimental protocols utilizing ERCC spike-ins on the effect of sequencing depth and on the limit of detection , confirmed high sensitivity of Smart-seq protocols and comparable but variable accuracy when compared to UMI-based methods36. Consistent with our findings this analysis also showed that sensitivity is highly dependent on sequencing depth, experimentally confirming our value for the optimal sequencing depth  whereby the increase in read depth from 1 million reads to 4.5 million reads per sample results in marginally increased sensitivity. Finally, UMI-based methods can be modified to obtained VDJ region of the TCR at the single cell level. For instance 10x Genomics has recently released a new protocol to sequence VDJ sequences from bar coded T cells (https://www.10xgenomics.com/vdj/). This approach however does not provide simultaneous analysis of gene expression and TCR repertoire from the same cell.This study focussed only on T cells and scRNA-seq protocols available that allow full-length sequencing of transcripts. Barcoded methods, such as those with microfluidics based technologies and unique molecular identifiers (UMIs) are restricted to sequencing of a small fragment of the mRNA transcript, thus limiting the detection of full TCR sequences. At the time of this analysis there were no studies that performed UMI-based protocols for T cell subsets. A recent study has utilised a cell line to benchmark four UMI-based protocols  against Smart-seq. 1, and Smart-seq. 2In conclusion, our results based on T cell data are consistent with benchmark studies on other cells, showing that the full-length scRNA-seq methods provide good accuracy, high sensitivity and larger potential for applications in T cell biology. Future development of barcoded technologies that allow full-length transcriptomic sequencing will allow the application of these technologies to a larger number of cells, enabling comprehensive study of the role of T cells in experimental models and human disease states.Raw data were downloaded from NCBI’s Gene Expression Omnibus and ArrayExpress Table .Simulated data were obtained by generating subset of reads from Dataset 1 in Table 37. For Trimmomatic we used the following parameters: Nextera adapters, leading = 3, trailing = 3, window length = 4, window quality = 15, average quality = 20, minimum length was chosen according to the read length of the dataset. Alignment of PE reads was performed with TopHat2. For the alignment, the default option was used, .PE reads were analysed for quality control using FastQC, and reads were trimmed using Trimmomatic38, using the detectGenes function to count and filter genes by FPKM value. Downstream analysis, which included Pearson’s correlation analysis, number of genes expressed, and gene expression analysis by gene categories, was performed with an in-house R script. Transcription factors and housekeeping genes have been selected from available list in the literature40.Gene expression was estimated with the pipeline available in Cufflinks 2.2.1, utilising CuffQuant with parameter–max-frag-multihits equal to 1, which allows maximum one alignment per fragment. Gene expression quantification (in FPKM) was normalised with CuffNorm using default parameters. Resulting FPKM values were manipulated in R using the package Monocle (version 2)30, which requires raw read counts as input data. The tool featureCounts was used to obtain the read counts, with the–primary option to allow only primary alignments. The dropoutCandidates Boolean matrix output by the determinDropoutoutCandidates method of CIDR is used to calculate the figures in Table dropoutCandidates matrix has a value of FALSE.Dropout analysis, principal coordinates analysis and clustering were performed using CIDRnCluster and wThreshold were set to be 3 and 6 respectively, while the other CIDR parameters were left as defaults. Within each cluster, the first two CIDR principal coordinates were used to calculate Euclidean distances between all pairs of samples, the squares of which sum to the within-class sum of squares.For clustering, the CIDR parameters Misclassification rate was used to evaluate the accuracy of clustering, which is defined as the number of misclassified cells divided by the total number of cells. To define misclassified cells, each CIDR cluster is associated with the ground truth cluster, which gives the biggest intersection, and those cells that are not in the intersection are counted as misclassified cells.41. A second method was used to validate the VDJPuzzle result using the program TraCeR21 (see Supplementary Text). VDJPuzzle algorithm is briefly outlined in the following steps (see41 for more details): for each single cell and for each chain: i) it aligns the reads to the full reference genome; ii) it extracts the reads that align to one known VDJ gene or constant region and assemble these reads using a de novo assembly algorithm (Trinity42); iii) all reconstructed sequences with a match to the IMGT database are collected in a preliminary TCR sequence identification; iv) the original reads are re-aligned (using bowtie 243) against the putative TCR sequences, to include additional reads that could have been lost in the first alignment;.v) resulting aligned reads aligning to the preliminary repertoire are assembled with Trinity and interrogated to IMGT with MigMap, a smart wrapper for IgBlast (https://github.com/mikessh/migmap).TCRαβ of the downloaded dataset were reconstructed using VDJPuzzle20.Successful reconstruction of a TCR from a single cell was defined as at least one complete and in-frame TCR sequence  identified in the IMGT database. The exact procedure was performed as previously reportedx represents the read length and y represents the sequencing depth. The obtained fitting values are The fit of the proportion of cells with successful TCRαβ reconstruction as a function of read length and sequencing depth was performed using a two-dimensional sigmoidal function implemented in the scipy package in python (the “curve_fit”)The scRNA-seq data analysed are freely available and accession numbers are provided in Table Supplementary Materials


Ensembles of driven or motile bodies moving along opposite directions are generically reported to self-organize into strongly anisotropic lanes. Here, building on a minimal model of self-propelled bodies targeting opposite directions, we first evidence a critical phase transition between a mingled state and a phase-separated lane state specific to active particles. We then demonstrate that the mingled state displays algebraic structural correlations also found in driven binary mixtures. Finally, constructing a hydrodynamic theory, we single out the physical mechanisms responsible for these universal long-range correlations typical of ensembles of oppositely moving bodies. et al. develop a model for two groups of motile bodies targeting opposite directions and show that the system exhibits critical behaviour as a function of particle density.Self-driven particles can drive the system out of equilibrium without the help of external forces. Here Bain  Should you want to mix two groups of pedestrians, or two ensembles of colloidal beads, one of the worst possible strategies would be pushing them towards each other. Both experiments and numerical simulations have demonstrated the segregation of oppositely driven Brownian particles into parallel lanes12346789111314131618In this communication, we address the phase behaviour of a binary mixture of active particles targeting opposite directions. Building on a prototypical model of self-propelled bodies with repulsive interactions, we numerically evidence two non-equilibrium steady states: a lane state where the two populations maximize their flux and phase separate, and a mixed state where all motile particles mingle homogeneously. We show that these two distinct states are separated by a genuine critical phase transition. In addition, we demonstrate algebraic density correlations in the homogeneous phase, akin to that recently reported for oppositely driven Brownian particlesN self-propelled particles characterized by their instantaneous positions ri(t) and orientations i=1, …, N . Each particle moves along its orientation vector at constant speed i=0 (right movers) or π (left movers) according to a harmonic angular potential We consider an ensemble of Tij. This type of model has been successfully used to describe a number of seemingly different active systems, starting from bird flocks, fish schools and bacteria colonies to synthetic active matter made of self-propelled colloids or polymeric biofilaments13212223242526rij=(ri−rj): as they interact particles turn their back to each other =B(1−rij/(ai+aj)), where B is a finite constant if rij<(ai+aj) and 0 otherwise. In all that follows, we focus on the regime where repulsion overcomes alignment along the preferred direction (B>1). The interaction ranges ai are chosen to be polydisperse to avoid the specifics of crystallization, and we make the classic choice a=1 or 1.4 for one in every two particles. Before solving 15In principle, oriented particles can interact by both forces and torques. We here focus on the impact of orientational couplings and consider that neighbouring particles interact solely through pairwise additive torques −2, and a sweep-and-prune algorithm for neighbour summation. We use a rectangular simulation box of aspect ratio Lx=2Ly with periodic boundary conditions in both directions. We also restrain our analysis to H=1, leaving two control parameters that are the repulsion strength B and the overall density N comprised between 493 and 197,300 particles.Starting from random initial conditions, we numerically solve We observe two clearly distinct stationary states illustrated in B, Although phase separation is most often synonymous of first-order transition in equilibrium liquids, we now argue that the lane and the mingled states are two genuine non-equilibrium phases separated by a critical line in the : zν=1.21±0.16.〈We do not have a quantitative explanation for this critical behaviour. However, we can gain some insight from the counterintuitive two-body scattering between active particles. In the overdamped limit, the collision between two passive colloids driven by an external field would at most shift their position over an interaction diameterg(r), is plotted in α and β the preferred direction of the populations (left or right), we find that the asymptotic behaviours of all pair correlation functions gαβ decay algebraically as We now evidence long-range structural correlations in this active-liquid phase, and analytically demonstrate their universality. The overall pair correlation function of the active liquid, B limit, the microscopic interactions are accounted for by a simplified scattering rule anticipated from ψα reads:To explain the robustness of these long-range correlations, we provide a hydrodynamic description of the mingled state, and compute its structural response to random fluctuations. We first observe that the orientational diffusivity of the particles increases linearly with the average density δρα around the average homogeneous state . Within a linear response approximation, they take the compact form:The convective term on the l.h.s stems from self-propulsion, the third term accounts for alignment with the preferred direction Jα describes the convection and the collision-induced diffusion of the α species, and where D and hα and ∇δρα. These simple observations are enough to set the functional form of The two anisotropic diffusion tensors T δρβ(−q)〉 has a similar form, q=0. Approaching q=0 from different directions yields different limits, which is readily demonstrated noting that x−3/2 and plotted versus the rescaled distance y/x1/2.with q→0, and the density correlations algebraic, only when a≠b. Inspecting x-direction while frontal collisions induce their transverse diffusion. As a result the x-position of the particles increase linearly with time, and their transverse position increases as ∼t1/2. We therefore expect the longitudinal and transverse correlations to be related by a homogeneous function of y/x1/2 in steady state as observed in simulations of both active and driven particles. Altogether these observations confirm the universality of the long-range structural correlations found in both classes of non-equilibrium mixtures.Different non-equilibrium processes can result in algebraic density correlations with different power laws, for example, ref. articles  and, basIn conclusion, we have demonstrated that the interplay between orientational and translational degrees of freedom, inherent to motile bodies, can result in a critical transition between a phase separated and a mingled state in binary active mixtures. In addition, we have singled out the very mechanisms responsible for long-range structural correlations in any ensemble of particles driven towards opposite directions, should they be passive colloids or self-propelled agents.Let us summarize the main steps of the kinetic theory employed to establish α particles along α particles are given by ∂tρα+∇·(ραVα)=0, is obtained by integrating θ and constrains The first term indicates that a collision with any particle located at Qα, vα and ρα is required to yield a self-consistent hydrodynamic description. Deep in the homogeneous phase, we make a wrapped Gaussian approximation for the orientational fluctuations in each population24vα in the mass conservation relation, leading to the mass conservation equation where the second term on the l.h.s is a convective term stemming from self-propulsion. The force field on24refs . As momeThe data that support the findings of this study are available from the corresponding author upon request.How to cite this article: Bain, N. & Bartolo, D. Critical mingling and universal correlations in model binary active liquids. Nat. Commun.8, 15969 doi: 10.1038/ncomms15969 (2017).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Interesting spectroscopic features on the interaction between imidazolium cations and halogen anions was also obtained from spectroscopic studies at IR frequencies (550–3300 cm−1). As far as the frequency of the intermolecular vibrational mode is concerned, we found the significance of the reduced mass in determining the intermolecular vibration frequency.The terahertz and infrared frequency vibration modes of room-temperature ionic liquids with imidazolium cations and halogen anions were extensively investigated. There is an intermolecular vibrational mode between the imidazolium ring of an imidazolium cation, a halogen atomic anion with a large absorption coefficient and a broad bandwidth in the low THz frequency region (13–130 cm On the other hand, a systematic study on the vibrational modes of room-temperature ionic liquids that have imidazolium cations and halogen anions as more basic systems has not been performed by using THz, FIR, and IR spectroscopy, although IR spectroscopic studies for some ionic liquids have been performed [I−], where C6 and mim stand for the carbon number of the alkyl-chain part and the methyl-imidazolium ring part of the molecular cation, respectively. An ionic liquid sample was put into an assembled cell when the THz-TDS and FIR measurements were conducted. Two 2.0-mm-thick plastic plates consisting of a cyclo-olefin polymer , which has a favorable transmittance and a refractive index over a wide THz frequency range, were used as cell windows. The sample thickness was controlled by a spacer, typically 60 μm thick, sandwiched between two plastic windows. Reference measurements without an ionic liquid were performed on the condition that the surfaces of the two plastic plates were in contact. A droplet of an ionic liquid sample was directly used for the ATR-IR measurements. A density functional theory (DFT) calculation was performed for the alkyl-methyl-imidazolium cations. The geometry was optimized at the B3LYP/6-31G(d) level of theory and then the infrared vibrational spectra and electrostatic potential maps were calculated at the same level of theory.The samples we used were room-temperature ionic liquids, consisting of a series of alkyl-methyl-imidazolium cations and halogen anions, as shown in 6mim+][I−], [C4mim+][I−], and [C3mim+][I−] obtained from both THz-TDS and FIR. The imaginary part of the dielectric constant (Im ε/M) and the absorption coefficient (α/M) normalized by the molar concentration are shown in the insets in −1), it was striking that the Im ε/M and α/M spectra were almost the same for [C6mim+][I−], [C4mim+][I−], and [C3mim+][I−]. A relatively large and broad band with a peak at 72.5 cm−1 was found in the α/M spectrum in the low THz frequency region. The data indicate that Im ε/M and α/M spectra are not affected by any kind of intramolecular vibration of the alkyl-chain parts of imidazolium cations. According to the calculation of the vibration spectra of imidazolium cations, some intramolecular vibrational modes have weak intensity as a motion of the whole imidazolium cation, including the alkyl-chain part, in the low THz frequency region, and therefore the calculated frequency and intensity of these modes depend on the alkyl-chain length , there were weak but discernible absorption bands in α (α/M) spectra at 225, 290, and ~425 cm−1 for [C6mim+][I−]; 210, 290 and ~425 cm−1 for [C4mim+][I−]; and 230, 280, 325, and ~425 cm−1 for [C3mim+][I−]. According to our calculations, some vibrations have week intensity, including the accordion-like motions of alkyl-chain parts, and the vibrational frequencies differ to some extent depending on the alkyl-chain length , two relatively strong absorption bands at the same frequencies (616 and 647 cm−1) were found for these ionic liquids. The peak position of 616 cm−1 was determined using the data from the ATR-FTIR spectra described later, because the peak position could not be identified due to the low signal-to-noise ratio in the region (590–630 cm−1) of the FIR spectra. These absorption bands inherently originate from the intramolecular vibrational modes of the skeletal vibration of the imidazolium ring, according to our calculations. Therefore, these two absorption bands are almost unaffected by the alkyl-chain length, which was confirmed by our calculations and experiments. In 3mim+][I−] > [C4mim+][I−] > [C6mim+][I−], meaning that the electric susceptibility, which depends on the number density and polarizability of the material, follows the same trend in the frequency region. The behavior of Im ε below 30 cm−1 in ngth see . It is dngth see . In part6mim+][Br−], [C8mim+][Br−], and [C10mim+][Br−]  spectrum was found in the low THz frequency region. Similarly, it is preferable to explain the absorption band according to the electrostatic interaction between [mim+] and [Br−]. In the mid THz frequency region, there were weak but discernible absorption bands due to the intramolecular vibrations of the alkyl-chain parts in α (α/M) spectra at 225, 290, and ~425 cm−1 for [C6mim+][Br−]; 215, 290, and ~425 cm−1 for [C8mim+][Br−]; and 215, 290 and ~425 cm−1 for [C10mim+][Br−]. In the high THz frequency region, two relatively strong absorption bands were found due to the intramolecular vibrational modes of the skeletal vibration of the imidazolium ring at the same frequencies (620 and 650 cm−1) for these ionic liquids. The magnitude of Re ε in the low-frequency region follows the trend, [C6mim+][Br−] > [C8mim+][Br−] > [C10mim+][Br−], and the behavior of Im ε below 30 cm−1 indicates the existence of a dielectric relaxation mode or librational motion for these ionic liquids. These features are similar to the cases of ionic liquids with [I−].see also . In the 6mim+][Cl−], [C8mim+][Cl−]  spectrum in the low THz frequency region. It is preferable to explain the absorption band according to the electrostatic interaction between [mim+] and [Cl−]. In the mid THz frequency region, there were weak but discernible absorption bands due to intra-molecular vibrations of alkyl-chain parts in a/M spectra at 225, 290, and ~425 cm−1 for [C6mim+][Cl−], and 290 and ~425 cm−1 for [C8mim+][Cl−], superimposed on the tail of the large and broad band. In the high THz frequency region, two relatively strong absorption bands were found due to the intramolecular vibrational modes of the skeletal vibration of the imidazolium ring at the same frequencies (628 and 655 cm−1) for these ionic liquids. The magnitude of Re ε in the low-frequency region follows the trend, [C6mim+][Cl−] > [C8mim+][Cl−], and the behavior of Im ε below 30 cm−1 indicates the existence of a dielectric relaxation mode or librational motion.see also . In the −1 for [C6mim+][I−], [C6mim+][Br−], and [C6mim+][Cl−]. In the low THz frequency region (13–130 cm−1), strong and broad absorption bands were found at 72.5, 92 and 122 cm−1 for [C6mim+][I−], [C6mim+][Br−], and [C6mim+][Cl−]. The ionic liquid with a heavier halogen anion exhibited absorption at a lower frequency, while the ionic liquid with a lighter halogen anion exhibited stronger absorption at a higher frequency. In the mid THz frequency region (130–500 cm−1), we can also recognize the intramolecular vibrations due to the accordion-like motions of alkyl-chain parts at almost the same frequencies. Such intramolecular vibrations in ionic liquids have not been identified so far. In the high THz frequency region, the two relatively strong absorption bands due to the intra-molecular vibrational modes of the skeletal vibration of the imidazolium ring clearly are frequency-dependent on the halogen anion species.et al. [I−], [C6mim+][Br−], and [C6mim+][Cl−], as well as the calculated IR spectrum of [C6mim+] from 550 to 3300 cm−1. The absorption coefficient cannot be well defined due to the ATR geometry, and therefore the IR spectra are not normalized by molar concentration. The calculated IR spectrum in 6mim+] and the halogen anion can be deduced by analyzing the IR spectra, because the halogen anion itself does not have a vibrational mode.−1 in −1 in −1 in −1 are attributable to typical symmetric and asymmetric stretching vibrations of methylene and methyl groups in the alkyl-chain part. The frequencies of these vibration modes are not affected by the species of halogen anion, indicating that the alkyl-chain part does not have a specific interaction with the halogen anions. We focused our attention on the region between 3000 and 3300 cm−1. The significance of the vibrational modes in this region has been pointed out in discussing the interaction between the imidazolium cation and the anion [I−]. Comparing +C(2)–H···Ahalogen− with +C(2)–H···Amolecule−, the frequency of the mode is strongly red-shifted, indicating that the interaction H···Ahalogen− is inherently stronger than the interaction H···Amolecule−. On the other hand, the frequency shift of the mode among halogen anions  is small. A peak at around 3135 cm−1 is attributable to C(4)–H and C(5)–H stretching vibrations with symmetrical movements to each other. The frequency shift of the mode among halogen anions  is small. A peak between 3040 and 3070 cm−1 is attributable to C(4)–H and C(5)–H stretching vibrations with asymmetrical movements to each other. It is known that this mode is sensitively affected by the position of a halogen anion near +C(2) . Considering the fact that the motions of the intramolecuar skeletal vibrations of [mim+] are affected by the interaction with halogen anions and the various vibrations of the alkyl-chain parts are hardly affected, as found in the mid and high THz and IR frequency regions, this idea seems to be valid. The electrostatic potential map of the cation as shown in −], 79.96 for [Br−], and 35.45 for [Cl−]. The reduced mass μ is calculated as 1/μ = 1/+]μ[mim + 1/−]μ with a mass of 280 and [C2mim+] with a mass of 97, the absorption band at 97 cm−1 was observed [2mim+][NTf2−] at 97 cm−1 is close to the absorption band of [C6mim+][Br−] at 92 cm−1. We considered the reduced mass μ of [mim+][Br−] as 40.8. This leads to the larger force constant k in [C2mim+][NTf2−], compared with k in [mim+][Br−]. Considering the interaction energies in both systems, it seems unlikely. One possibility to solve the discrepancy is to consider the effective masses both for cation and anion involved in the intermolecular vibration, because the presence of localized and directional hydrogen bonding in [C2mim+][NTf2−] was shown [In the case of an imidazolium ionic liquid containing a molecular anion, the significant contribution of the force constant for the frequency shifts in the intermolecular vibrational bands is pointed out ,17. In tobserved . The redobserved . The absas shown ,31, the Far infrared spectroscopic studies on tetra-alkylammonium halide crystals and their theoretical analysis point out the significance of reduced mass in determining the intermolecular vibration frequency .The application of other spectroscopic techniques such as Raman spectroscopy ,33, optiIn conclusion, many interesting intramolecular and intermolecular vibrational modes affected by the interplay between positively charged imidazolium molecules and negatively charged halogen atom in the liquid states were found over a wide frequency range. The data provide us with the microscopic picture of the interaction between a specific part of the imidazolium ring and the halogen anion and the little interaction with the alkyl-chain part of the imidazolium cation. In these systems, we found the significance of the reduced mass in determining the intermolecular vibration frequency. Our systematic data and analysis for ionic liquids consisting of an imidazolium cation and a halogen anion could be useful in elucidating the nature of ionic liquids with anion molecules as more complex systems.


OC accumulation rates displayed similar coeval variation with temperature, mirroring both changes in aquatic production and terrestrial carbon export. Increase in sediment organic content over the 20th century together with high inferred aquatic UV exposure imply that the 20th century increase in OC accumulation is primarily connected to elevated lake production rather than terrestrial inputs. The changes in the supply of autochthonous energy sources were further reflected higher up the benthic food web, as evidenced by biotic stable isotopic fingerprints.Widespread ecological reorganizations and increases in organic carbon (OC) in lakes across the Northern Hemisphere have raised concerns about the impact of the ongoing climate warming on aquatic ecosystems and carbon cycling. We employed diverse biogeochemical techniques on a high-resolution sediment record from a subarctic lake in northern Finland (70°N) to examine the direction, magnitude and mechanism of change in aquatic carbon pools prior to and under the anthropogenic warming. Coupled variation in the elemental and isotopic composition of the sediment and a proxy-based summer air temperature reconstruction tracked changes in aquatic production, depicting a decline during a cool climate interval between ~1700–1900 C.E. and a subsequent increase over the 20 Concomitant effects on carbon utilization in the benthic food web were investigated from the stable isotopic composition of fossil invertebrate (Cladocera) chitin. To estimate changes in solar radiation attenuation and lake water UV transparency, controlled by terrestrial OC input, the degree of UV absorbance of benthic Cladocera was assessed. We expected to find temperature-driven increase in the export of terrestrial OC in association with the 20th century warming, contributing to an increase in the sediment carbon pools and affecting carbon utilization patterns and UV transparency in the lake. The results build towards an improved understanding of the influence of global change on aquatic carbon dynamics in northern lakes that constitute an integral element in the global carbon cycle.With this study we attempt to build towards a better understanding of the link between carbon dynamics and temperature in northern lakes by examining high resolution temporal variations in sediment OC pools prior to and under the recent warming in subarctic Lake Námmájávri at the Fennoscandian treeline . Elementth until the early 20th centuryet al.th century in northern Finland, followed by a distinct increase particularly over the latter half of the 20th century. In concert, contemporary monitoring data from northern Finland (available 1960s onwards) depicts increasing mean annual temperature over recent decadesOur record depicts synchronous variations in temperature  and the 16118δ13COM values in Lake Námmájávri (mean −23.3‰) resemble those commonly associated with diffusion-limited benthic autochthonous production 2113C-depleted (~−27‰), but may yield values that overlap with the benthic signalδ15N values (mean −0.4‰) in the sediment likely reflect the presence of N-fixing cyanobacteria252825Bivariate correlations and multivariate analyses indicated a temperature coupling both with the sediment OC content and biogeochemical composition , Table 1ri mean −.3‰ resemri mean −.3‰ resempleted ~−‰, but maδ13COM . The synchronous variations likely mirror increased aquatic primary production under warming temperatures, resulting in progressive 13C and 15N enrichment of the sediment OM as the lake water C and N pools become increasingly enriched in the heavier isotopesδ13COM and δ15NOM values may additionally be related to weakened physiological fractionation against the heavier isotopes as the lake water C and N pools become depleted upon biological uptakeδ13COM and δ15NOM and elevated C/N values during the coolest LIA phase between ~1700–1900 C.E. imply lower autochthonous contribution to the sediment OM.A positive correlation between the inferred temperature and the δ13COM , Table 1the core . Similarthe core , 3, 4, tth century588th and 20th centuries  is a relative measure that does not take into account compositional changes nor accommodate for changes in sediment delivery, as also evidenced by the disparity between OC content and OCAR in Lake Námmájávri . This di content . In line content  and 4, tanalyses , Table 1th century likely reflect initial temperature stimulus on aquatic production, driven primarily by improved light availability under lengthened ice-free period. The following catchment response is likely to not only increase the export of OC but also of allochthonous nutrients that may further promote lake production12th century  of benthic Cladocera (family Chydoridae) that constitute a central link in aquatic carbon transfer from primary producers to higher trophic levels. The δ13CChd and δ15NChd followed a pattern very similar to the isotopic composition of the bulk sediment (15N-enriched compared to the sediment (mean difference 0.4 ± 0.3‰), which could be attributable to the more efficient excretion of 14N relative to 15N during metabolization4615N . Typical trophic enrichment for N between the consumer and food source is +2–4‰δ15N values of the cladoceran diet are relatively close to those of the bulk sediment. For δ13C, the offset between exoskeletons and whole individuals, taphonomic processes, and trophic fractionation generally have a minimal effect4613C-depleted relative to the bulk sediment (mean difference −0.9 ± 0.7‰) and considering the effect of the acid treatment the negative offset is likely to be slightly larger. 13C-depletion in consumers relative to their diet has been observed in earlier studies13C depleted organic compounds (such as lipids), or to preferential utilization of terrestrial detritus.The temperature fluctuations and consequent changes in the relative supply of autochthonous OC were also mirrored at the consumer level, as evidenced by the stable isotopic composition . The surface sediment δ13COM and δ15NOM in the lakes mirror primarily variation in the contribution of carbon from terrestrial sources and aquatic benthic production to the sediment carbon poolsδ13C and δ15N in the sediment, and in the benthic fauna, across diverse catchment types is strongly connected to terrestrial influence. In Lake Námmájávri, DOC and CDOM concentrations were among the lowest in the regional lakes set, which likely explains why the stable isotopic fingerprints in the sediment profile seem to track primarily in-lake processes . To allow comparison with the pelagic zone, the stable isotopic composition  of planktonic Cladocera (family Bosminidae) was analyzed from the surface sediments, showing marked stability in contrast with the benthic community  treeline. Mountain birch (Betula pubescens ssp. czerepanovii) woodland dominates at lower elevations in the topographically diverse fell terrain to an elevation of around 250 m. The lake lies in a depression surrounded by steeply sloping fells to the north and south, draining water from a large catchment area (900 ha) with an overall altitudinal gradient of around 200 m. The basin is hydrologically open, with a narrow inlet and an outlet stream, and is connected to two smaller lakes upstream  is a small and shallow oligotrophic lake situated in the treeline ecotone in northern Finnish Lapland  some 60 upstream . The sur® plastic bags at 4 °C prior to the analyses. The sediments were analyzed for loss-on-ignition following standard methodsr2 = 0.97) in the surface sediments of lakes in the regionδ13COM, δ15NOM) of sediment OM were analyzed from freeze-dried and homogenized sediments. The analyses were run in duplicate and mean values were used in the data analyses. On average, duplicate measurements of δ13COM differed by 0.4‰ (three samples exceeding 1.0‰), δ15NOM by 0.1‰ (one sample exceeding 0.5‰), C by 0.1‰, and N by 0.01‰. Determination of the stable isotopic composition of carbon and nitrogen in chitinous cladoceran (Chydoridae and Bosminidae) exoskeletons  was done following Perga® water, and cladoceran remains (carapaces and headshields) were picked with fine forceps under stereomicroscope at 40× magnification. The analysis was performed at intervals of 2 cm (every other sample), hand picking approximately 500‒1000 Chydoridae remains to yield a sample mass of ≥0.2 mg. The samples consisted mostly of Alona affinis remains, supplemented with low amount of remains of other benthic taxa to ensure adequate sample mass. The topmost 7 cm were excluded due to scarcity of remains. Stable isotopic analysis on Chydoridae remains was additionally performed on the surface sediments of 11 lakes in the regional lake setEubosmina longispina) were picked and analyzed separately. The stable isotope ratios are expressed relative to standard as the delta notation δ = Rsample/Rstandard − 1 × 1000, where R equals 13C/12C for carbon and 15N/14N for nitrogen. The respective standards used were Vienna Pee Dee Belemnite (VPDB) and atmospheric nitrogen (AIR). Analytical precision (expressed as standard deviation) was determined based on internal laboratory working standards for bulk sediment samples  and cladoceran remains . For the bulk sediment samples, standard deviations between the replicate reference standards were 0.4‰ (δ13COM), 0.3‰ (δ15NOM), 0.2% (C) and 0.03% (N). For the chitinous remains, the corrensponding values were 0.4‰, 0.05‰, 0.2% and 0.1%. The C content of the chydorid exoskeletons was also assessed to ensure that the changes in δ13CChd are not related to C degradationA sediment core was retrieved in July 2014 at the center of Lake Námmájávri  at a watet al.5657582boot) of 0.86, a root mean squared error of prediction (RMSEP) of 0.86 °C, and a maximum bias of 0.77 °C. Lake Námmájávri was removed from the calibration set to avoid a bias in the reconstruction. A direct gradient analysis, canonical correspondence analysis (CCA), was used to assess the strength of temperature in determining chironomid community composition in the training set. The ratio of the first constrained eigenvalue (λ1) to the second unconstrained eigenvalue (λ2) indicates the relative significance of a specific variable in explaining the cumulative variance in the species data. In the present training set, λ1/ λ2 was >1 (1.178), suggesting that temperature is an important ecological determinant for the chironomid distribution and may be used in quantitative inference modelsth percentile of all squared chord-distances in the modern calibration data were determined. These distances were then compared to the distance between each fossil assemblage and its most similar assemblage in the modern dataset and used to define ‘no close’ analogues.Subsamples for fossil chironomid analysis were prepared applying standard methodsAlona affinis) carapaces following the protocol established by Nevalainen & RautioUV absorbance was measured from fossil cladoceran  dating of four terrestrial macrofossils (137Cs) dating of bulk sediment  dating was additionally employed, but no reliable age estimates were obtained owing to low activities (≤0.2 Bq g−1) typical for northern lakes. The radiocarbon dates were calibrated using Clam 2.2Core chronology was established based on accelerator mass spectrometry (AMS) radiocarbon (ofossils  and radisediment . 14C ageδ13COMδ15NOM) and to detect relationships to the chironomid-inferred mean July air temperature and lake water UV transparency (UV absorbance of benthic Cladocera). Variance partitioning analysis (VPA) with Monte Carlo permutation tests (permutations set at 999) were further used to assess which fraction of the variance in the geochemical data is explained by the two predictor variables. Additionally, pairwise correlations between the variables were assessed with parametric correlation tests. False discovery rate (FDR) using the Benjamini-Hochberg procedure was employed to correct for multiple comparisons, setting the q-value at 0.01. Prior to the analyses, Shapiro-Wilk and skewness were assessed together with visual inspection of the data to check for data normality. The predictor variables and response variables that departed from normality were square root transformed. Response variables were centered and standardized for the ordination. The topmost sample (0–1 cm), representing the past ~10 years, was excluded from the data analyses to account for the effects of incomplete mineralization.Constrained direct gradient analysis, redundancy analysis (RDA), was employed to summarize variation in the geochemical composition of the sediment .


Among them, we discovered acid-induced oscillations in the pH of SCM (pHSCM), observed in 24% of polyps examined. In addition, we discovered acid-induced pH up-regulation waves in 21% of polyps examined, which propagated among SCMs after exposure to acidified seawater. Our results showed that corals can regulate pHSCM more dynamically than was previously believed. These observations will have important implications for determining how corals regulate pHSCM during calcification. We propose that corals can sense ambient seawater pH via their innate pH-sensitive systems and regulate pHSCM using several unknown pH-regulating ion transporters that coordinate with multicellular signaling occurring in coral tissue.Corals build their skeletons using extracellular calcifying fluid located in the tissue–skeleton interface. However, the mechanism by which corals control the transport of calcium and other ions from seawater and the mechanism of constant alkalization of calcifying fluid are largely unknown. To address these questions, we performed direct pH imaging at calcification sites  to visualize active pH upregulation in live aposymbiotic primary coral polyps treated with HCl-acidified seawater. Active alkalization was observed in all individuals using vital staining method while the movement of HPTS and Alexa Fluor to SCM suggests that certain ions such as H SCM), facilitate the conversion of bicarbonates to carbonates, and increase the aragonite saturation state (Ωarag) followed by facilitation of skeletal growth at the site of calcification. However, the physicochemical conditions in the SCM  are largely unknown.Coral calcification is believed to occur in a physiologically controlled environment in the extracellular calcifying fluid located in the tissue–skeleton interface [subcalicoblastic medium (SCM)]232+ + HCO3− → CaCO3 + H+3. The active removal of protons from the SCM leads to higher pHSCM (approximately pHNBS: 8.6–10.0)12) and is recognized as a severe threat to calcifying organismsarag, but also decreases in the pHSCM and calcification789Favia fragum reared under very low Ωarag conditions (Ωarag = 0.22) were able to create aragonite crystals beneath the polypCalcification generates protons in the SCM via the chemical reaction Cain vivo pH imaging method using live coral tissues permits direct pH measurements at calcification sites, providing detailed information of pH dynamics in coral tissue1SCM during coral calcification responds to ambient seawater conditions, such as changes seawater pHThe use of boron isotopes has provided details about the pH conditions for calcification, but this usage relies on an indirect geochemical technique using a boron isotope pH proxy and cannot reveal the mechanisms of pH upregulation by corals at calcification sites12SCM, we performed a new time-lapse pH imaging method monitoring change in pH of the calcifying fluid during seawater acidification7892-driven ocean acidification from the aspect of marine CO2 chemistry. However, we recognize that our experimental results would help us to understand the physiological responses of corals to acid stress such as daily changes in seawater pH and near-future ocean acidification. We discovered novel pH upregulation, acid-induced oscillations of pHSCM, and occasional acid-induced pH upregulation waves (velocity: 1–6 μm/s), which propagated among the SCMs induced by surrounding seawater acidification. In the present study, we have shown that corals can regulate pHSCM more dynamically than was previously believed, which would be regulated by several types of pH-regulating ion transporters that coordinate with multicellular signaling in coral tissue.To study the regulation of pHAcropora digitifera3 structures  of SCM during calcification. We used 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS)A. digitifera had the ability to alkalize their SCMs (32−) concentration and to promote the precipitation of CaCO31SCM dynamics without major effects on normal developmental processes in aposymbiotic coral primary polyps.Coral primary polyps without symbiotic algae of eir SCMs 2− concenSCM and calcification sensitivity to acidified seawater were observed in adult Stylophora pistillataSCM values in some defined regions of interest . Acidified HPTS containing seawater was labeled using Alexa Fluor® 568 dye to simultaneously monitor the putative diffusing H+ into SCM via the paracellular pathway. Alexa Fluor® 568 dye is the red fluorescent anionic compounds  which cannot pass through the cell membrane and have no overlapping fluorescence with HPTS for pH measurements in our experimental system .Four minutes after the start of the experiment, acidified seawater was added and red fluorescence from Alexa Fluorthe SCMs . When amthe SCMs , but thento SCMs : 10 min,nto SCMs , suggestseawater . ApproxiSCM  were detected approximately 90 min after the start of the experiment in this individual polyp  in four of the 19 coral primary polyps. To characterize the behavior of the pH regulation waves, we evaluated a representative case of polyp tissue in which a pH wave crossed from the upper left to the lower right . We founte arrow .2+ channels, Ca2+ pumps, and GAP junctions, that are major components of the human ion trafficking system and have also been identified in the coral genomic data342+ oscillations simultaneouslySCM alkalization and pHSCM response to ambient seawater) is presumably coordinated by multicellular calcium signaling throughout the calicoblastic cells. These multicellular cell-to-cell communication may play a significant role in balancing the pH homeostasis of entire calcifying tissue during the skeletal formation and growth. The pHSCM alkalization can be partly explained by the activation of ATP-driven Ca2+/H+ antiporters  located at the plasma membrane3SCM  can be achieved only via activation of Ca2+-ATPase.We assume that the pH wave propagation and pH oscillation observed in corals might be mediated by intercellular calcium signaling, given that cytosolic calcium signaling is a general phenomenon of signaling in excitable and non-excitable cells3031328293334SCM decrease (0.1–0.3 pH units from the ambient seawater pH) were observed 15 min after the start of the experiment  within a 2-min interval (17–19 min after the start of the experiment) and suddenly stopped alkalization at 20 min  has been reported344Despite the ambient seawater pH decrease to approximately 7.4, more extreme pHt 20 min : ROI 2, SCM more dynamicaly than they were previously believed, suggesting that pH-sensing and -regulating mechanisms underlie coral calcification. We propose that several types of pH-sensitive ion transporters regulate alkalization of SCM in a coordinated manner. Understanding the pH upregulation of corals observed in this study will be essential for predicting how they regulate pH at the calcification site and how they respond to ongoing ocean acidification. In addition, our observations suggest not only that pHSCM dynamics were regulated by surrounding calicoblastic epithelium cells but also that the pH among SCMs was coordinated at the tissue level via long-range multicellular signaling beneath the primary polyp. These findings pave the way for future studies of the multicellular regulation mechanisms involved in intercellular calcium signaling during skeletal formation. However, we could not clearly observe intracellular calcium signals because of the difficulty of monitoring these signals in the presence of autofluorescence from coral tissue or staining of calicoblastic epithelium cells with fluorescent calcium indicators31In summary, we found that corals can regulate pHA. digitifera, which is one of the most common species in the Ryukyu Islands of JapanA. digitifera were collected from a fringing reef at Sesoko Island, Motobu-cho, Okinawa, Japan. The colonies were kept in a running seawater tank under natural light conditions at Sesoko Station, Tropical Biosphere Research Center, University of the Ryukyus, Okinawa, Japan. Coral spawning occurred at night around the time of the full moon in the spring and summer seasons of 2015. Gametes were collected after spawning, as described by Inoue et al.Acropora planulae and is a useful tool for studies of Acropora larval metamorphosis. Approximately 10–20 larvae were placed in a glass-based dish  with 40 μL of filtered seawater (FSW: pore size 0.22 μm). Next, a 10-μL aliquot of 2 × 10−4 M Hym-248 in FSW was added to the dish and the larvae were incubated for 2 h to induce metamorphosis. Larvae that settled at the seawater surface and on the side of the dish were removed. The pH of the seawater was measured with a portable pH meter  against a total hydrogen ion concentration scale44T) using sodium hydroxide (NaOH). This solution was then diluted with FSW and buffered to pH 8.1 with NaOH to obtain a final concentration of 1 mM . After a 2-h incubation period with Hym-248, the solution was made to a volume of 2000 μL with FSW–HPTS. The specimens were incubated with FSW–HPTS in an incubator  in the dark at 27.0 ± 0.1 °C prior to pH imaging. Bright-field, dark-field, and polarization images were acquired with a Keyence VHX-2000 digital microscope .The scleractinian coral SCM was induced with acidified HPTS solution containing Alexa Fluor® 568 . Before the start of the experiment, 1000 μL of FSW–HPTS was gently extracted. During pH imaging, a mixed solution of 1000 μL of acidified HPTS  and Alexa Fluor® 568 (20 μM) was added 4 min after the start of recording to label the adding acidified FSW–HPTS. The dual-excitation ratiometric indicator HPTS was excited at wavelengths of 405 and 440 nm, and fluorescence was detected at 510–530 nm. Alexa Fluor® 568 was excited at 561 nm and fluorescence was detected at 610–640 nm 1 s after HPTS fluorescence was detected. Intervals were 1 min apart. pH calibration was performed by determining the ratio of HPTS fluorescence in FSW containing 1-mM HPTS adjusted with HCl and NaOH to the range of pH 6–9 at 25.0 ± 0.1 °C  was used to measure the velocity of pH waves.We used an inverted confocal imaging system  equipped with a high-resolution galvano scanner and operated with NIS Elements software . A CFI Plan Apo × 10 objective lens  was used to capture the whole image of the bottom of the coral tissue. The screen display resolution for viewing confocal microscope images was 1024 × 1024 pixels (0.86 μm = 1 pixel). Primary polyps at 14–18 h after metamorphosis were placed on a glass-based dish at room temperature (27 ± 0.2 °C). An acid-induced biological response in pH± 0.1 °C . We coulHow to cite this article: Ohno, Y. et al. An aposymbiotic primary coral polyp counteracts acidification by active pH regulation. Sci. Rep.7, 40324; doi: 10.1038/srep40324 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.