During the recent “Great Recession,” many families in the United Kingdom experienced increased financial strain (FS). The aim of this study was to determine if increases in FS, occurring over the period of the “Great Recession,” were associated with increased risks of persistent and relapsed tobacco use among parents.RR), adjusted RRs (aRR), and 95% confidence intervals for three outcomes: “persistent tobacco use,” “new reported tobacco use,” and “relapsed tobacco use.”We analyzed the Millennium Cohort Study, a longitudinal study of 18819 children born in the United Kingdom between 2000 and 2002. Surveys at 7  and 11 years  spanned the “Great Recession.” Three measures of increased FS were defined; “became income poor” (self-reported household income dropped below the “poverty line” between T1 and T2); “developed difficulty managing” ; “felt worse off” . Poisson regression was used to estimate risk ratios (aRR = 2.17 [1.83–2.57]) or “new reported tobacco use” (aRR = 1.72 [1.04–2.83]). Ninety-five percent of “new reported tobacco users” had evidence of prior tobacco use suggesting the majority were “relapsed tobacco users.” Similar patterns were seen for those who “developed difficulty managing” and “felt worse off.”Parents in households which “became income poor” over the period of the “Great Recession” were significantly more likely to report “persistent tobacco use” (Increased tobacco use among financially strained families has the potential to widen inequalities and undermine the public health policies that have had positive impacts on tobacco consumption in the United Kingdom.While several studies have shown that FS is associated with a higher prevalence of tobacco use, heavier smoking, and relapsed tobacco use, most of this work used cross-sectional data and none has focused on parents. We used longitudinal data from the UK Millennium Cohort Study, between 2008 and 2012, to examine the association between FS and parental smoking. We show that parents who experienced increased FS, over the period of the “Great Recession,” were more likely to continue using tobacco or to relapse. FS has been associated with a higher prevalence of tobacco use and heavier smoking.8 proposes that tobacco is used to relieve the negative emotions resulting from stress exposure. Qualitative research by Graham9 suggested the major reasons for relapse among a sample of lower socioeconomic mothers, who had previously given up smoking, were difficulty coping with everyday problems, stress, and financial pressures.The “tension-reduction hypothesis”10–13 This is a time when many families in the United Kingdom experienced an increase in FS. Literature examining tobacco use among adults, following the “Great Recession,” found that smoking was more common in those experiencing increased FS14 and inequalities in smoking increased.15 However, no study has focused on parents. Parental smoking is associated with higher rates of respiratory disorders among children,17 and those with a smoking parent are more likely to initiate smoking as adolescents.19 The pressures of providing for dependent family members during times of economic hardship might increase FS more for parents than for other adults, and this may impact on smoking behavior.In 2008, the United Kingdom entered “technical economic recession” in the context of a global financial crisis. The years following were characterized by rising unemployment, a fall in real wages, and rising levels of absolute poverty.The aim of this study was to determine if increases in household FS , occurring over the period of the “Great Recession,” were associated with increased risks of persistent or relapsed tobacco use among parents.www.cls.ioe.ac.uk/MCS). Surveys carried out when the MCS children were aged 7  and 11 years  spanned the period of the “Great Recession.” At age 11 years, 69.7% (n = 13112) of the original sample took part. This included 11387 natural mothers (n = 11220) and fathers (n = 167) who were the same main respondent at T1 and T2. This was our main working sample. Prior smoking history was also assessed for 9640 natural mothers or fathers who had been the same main respondent at all prior sweeps, in a subanalysis.We examined data from the Millennium Cohort Study (MCS), a longitudinal study of children born in the United Kingdom between 2000 and 2002. The original sample included 18296 singleton children. To date, MCS data are available for analysis at age 9 months, 3 years, 5 years, 7 years, and 11 years. The information collected includes a wide range of parental-reported sociodemographic and health factors (more information on the MCS can be found at Three measures of increased FS between ages 7 (T1) and 11 years (T2) were defined, each capturing different aspects of FS.20 The comparator group were those who “stayed nonpoor” .Household income was ≥60% of contemporary median at T1  and <60% of contemporary median at T2 . Incomes were reported by parents and equivalized according to Organization for Economic Cooperation and Development (OECD) scales.Main respondents were asked at T1 and T2, “How well would you say you are managing financially these days?”. Possible responses were (1) living comfortably, (2) doing alright, (3) just about getting by, (4) finding it quite difficult, and (5) finding it very difficult. An increase in household FS was defined as going from a score of 1–3 at T1 to 4/5 at T2. In the analyses, the comparator group were those who “did not report difficulty managing” .Main respondents were asked at T2, “Compared with the time of the last interview would you say that you are better or worse off financially or about the same?”. Possible answers included (1) a lot better off, (2) a little better off, (3) about the same, (4) a little worse off, and (5) a lot worse off. An increase in FS was defined as stating you were “a little” or “a lot worse off,” compared with T1. The comparator group were those who felt their finances were “about the same.”Households which remained financially strained, according to our definitions, at T1 and T2 or moved out of FS at T2 were excluded from the analyses. All measures of increased FS were based on parental report.Main respondents were asked at T1 and T2, “Do you use tobacco products such as cigarettes, cigars, a pipe or chewing tobacco at all nowadays?”. The sample was limited to natural parents who had been the same respondent at both T1 and T2 to ensure consistency.Those who reported tobacco use at both timepoints were considered “persistent tobacco users.” “New reported tobacco use” was defined as parental report of tobacco use at T2, which was not reported at T1. The majority of “new reported tobacco use” occurred in parents who had an identifiable history of tobacco use at interviews prior to T1. We therefore carried out an additional analysis examining “relapsed tobacco use.”In all analyses, the reference group was those who did not use tobacco at both timepoints and those who “gave up” between T1 and T2. Less than 1% were missing tobacco use data at T1 or T2.21 for “persistent,” “new,” and “relapsed smoking” according to the three measures of FS. We adjusted our analyses for lone parenthood (one parent household at T1), ethnicity , maternal level of education at 9 months (degree level or above), and parental age at T1 .Poisson regression was used to estimate unadjusted and adjusted risk ratios and 95% confidence intervalsAnalyses were conducted in Stata/SE 13 , using “svy” commands to account for clustered sampling design and attrition. Data were downloaded from the UK Data Service, University of Essex, and University of Manchester, in April 2014.n = 2905) of main respondents reported tobacco use at T1, and 25% (n = 2614) of the main respondents reported tobacco use at T2. Twenty-eight percent (n = 3176) of main respondents were below the poverty line (“income poor”), and 43% (n = 4674) reported difficulty managing financially. At T2, 19% (n = 2070) of main respondents were below the poverty line, 47% (n = 5195) reported difficulty managing financially, and 36% (n = 4059) felt worse off.At T1, 29% (n = 5206/13005) of all households experienced an increase in FS. Those who “became income poor” made up the smallest proportion (9.4%), and those who “felt worse off” made up the largest (89.6%).Between T1 and T2, 39.2%  of these “new reported tobacco users” had evidence of prior tobacco use based on data from MCS interviews prior to T1, suggesting that the majority were “relapsed users.” The association between FS stain and relapsed tobacco use was similar to that seen for new tobacco use  , and it is possible that this bias has not been fully accounted for. Parental report of smoking may also have been underestimatedTobacco use is unequivocally bad for parental and child health. Parents experiencing increases in FS may find it more difficult to quit tobacco use; in addition, those who have previously quit may be more likely to relapse. Measures to buffer families from FS or increased investment in smoking cessation, during times of widespread FS such as economic recessions, may help reduce this risk.Research at the UCL Institute of Child Health and Great Ormond Street Hospital for Children receives a proportion of the funding from the Department of Health’s National Institute for Health Research Biomedical Research Centres funding scheme. The Millennium Cohort Study is funded by grants to former and current directors of the study from the Economic and Social Research Council  and a consortium of government funders. AP was funded by a Medical Research Council fellowship (MR/J012351/1). CMK was funded by a NIHR Academic Clinical Fellowship. All researchers were independent of the funders. The funders, original data creators, depositors, copyright holders, and data funders played no part in the study design, analysis or interpretation of the data, writing the report, or the decision to submit for publication.None declared.


Hurricane Patricia in 2015 was the strongest Pacific hurricane to make landfall in Mexico. Although Patricia fortuitously spared major cities, it reminded us of the threat tropical cyclones (TCs) pose in the eastern North Pacific (ENP) and the importance of improving our understanding and prediction of ENP TCs. Patricia’s intensity and the active 2015 ENP hurricane season have been partially attributed to the strong El Niño in 2015, however there is still a lack of fundamental understanding of the relationship between El Niño-Southern Oscillation (ENSO) and ENP TCs. Here, we demonstrate that ENSO drives intrabasin variability of ENP TCs, with enhanced (reduced) TC frequency in the western portion of the ENP during El Niño (La Niña), but reduced (enhanced) TC frequency in the eastern nearshore area, where landfalling TCs preferentially form. This intrabasin difference is primarily driven by the Central American Gap Winds (CAGW), which intensify (weaken) during El Niño (La Niña), producing low-level anticyclonic (cyclonic) relative vorticity anomalies and thus an unfavorable (favorable) environment for TC genesis. These findings shed new light on the dynamics linking ENP TC activity to ENSO, and highlight the importance of improving CAGW representation in models to make skillful seasonal forecasts of ENP TCs. TC landfalls on the Pacific coast of Central America and Mexico are relatively infrequent due to the tendency for westward/northwestward TC trajectories. However, those TCs that do make landfall can bring catastrophic flooding, especially when TC-associated winds and moisture interact with mountainous orography5. For example, significant coastal flooding was triggered by Hurricanes Pauline in 1997 and Patricia in 2015. The latter is the strongest hurricane on record for the Western Hemisphere and inflicted an estimated $460 million USD damage across Mexico and Southern Texas7. Observed historical TC tracks in the ENP indicate that all landfalling TCs formed east of 116°W  of the ENP has both outstanding scientific motivation and profound socioeconomic implications.The ENP basin 9, and is a critical predictor in seasonal TC forecasts11 During El Niño, vertical wind shear over the ENP is reduced in response to anomalously warm eastern-central Equatorial Pacific sea surface temperature (SST), which tends to favor above-normal ENP TC activity12. Anomalous eastern Pacific ocean heat content during El Niño can also affect TC intensity13. However, whether there is a statistically robust relationship between ENSO and observed TC activity over the ENP has been called into question14. By dividing the ENP into Western Development Region (WDR) and EDR, recent studies16 found that only TCs that originated in the WDR are robustly correlated with ENSO , with more frequent and intense TCs observed during El Niño than La Niña. Locations of TC genesis and dissipation within the ENP are also characterized by a westward shift during El Niño compared to neutral ENSO and La Niña17. Such a TC response in the WDR has been attributed to changes in SST and mid-tropospheric relative humidity during ENSO18. However, ENSO’s impact on TCs in the EDR, which have a much higher probability to make landfall along the Pacific coast of Central America, has not been thoroughly investigated. There is currently no consensus on whether and how ENSO can exert an influence on TCs in the EDR.El Niño-Southern Oscillation (ENSO) is the most dominant climate mode on interannual timescales19, to relate ENP TC variability with ENSO indices16. However, few studies explored the influence of ENSO on the spatial distribution of TCs within the ENP, and the associated mechanism. As will be demonstrated below, a distinctive signature of ENSO’s impact on ENP TCs is an east-west spatial variation in TC activity. Such a feature cannot be understood using area-integrated analyses, which average out the opposite changes of TC activity in different parts of the basin. To address this issue, we carried out analyses focusing on ENSO’s impact on the spatial distribution of TCs within the ENP. We note that the boundary separating the EDR and WDR in our study is set at 116°W, following a previous study8. However, our analyses do not include Central Pacific TCs between 180° and 140°W, because the focus of this study is on the eastern part of the ENP near the coastline where mountain influences are potentially greater. Thus our WDR extends only to 140°W, rather than to the dateline8.Many previous studies on ENSO’s impact on ENP TCs used area-integrated measures, such as TC counts, TC days and the power dissipation index (PDI)We first made a composite of TC genesis location and track density for all El Niño and La Niña events during the period from 1970 to 2015 and compared the results to the climatological genesis location and track density for this period. 13 El Niño and 11 La Niña hurricane seasons were identified based on the 75th and the 25th percentiles of the Niño3.4 index  during El Niño (La Niña). These changes are similar in magnitude to those observed in the Caribbean and Atlantic during ENSO10. This ENSO-related ENP TC activity change in the nearshore area is also consistent with a previous study20.Similar spatial variability of ENP TCs, but opposite in sign, occurs during La Niña, with an expected decrease of TC activity in the WDR and an increase in the EDR Fig. . These f21; details in Methods) using the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis  and its extension, the Climate Forecast System version 2 . We chose CFSR and CFSv2 because they produce a more realistic representation of fine-scale atmospheric circulation features over the EDR24 than other reanalysis products. However, owing to the shorter record length of CFSR and CFSv2 data, only 11 El Niño and 7 La Niña hurricane seasons were identified during the 1979–2015 period. But, the TC activity response to El Niño and La Niña is insensitive to changes in the record length  . Over much of the ENP, the El Niño-induced changes in vertical wind shear and hurricane maximum potential intensity provide more favorable conditions for tropical cyclogenesis  GPI anomalies during El Niño (La Niña) show a well-defined structure extending westward from the Sierra Madre topographic gap areas, especially near the Isthmus of Tehuantepec , and the depth of these gaps can approach ~1000 meters vertically , along with the corresponding SST. Both CAGW at TT and PP are clearly visible in the climatology, but the northerly TT jet is stronger and more effectively cools local SSTs. The CAGW at TT follows anticyclonic arcs downwind from the coast. In contrast, the CAGW at PP is more zonal because of the orientation of topographic gaps and the influence of steady trade winds. ENSO modulates the strength of the CAGW31, with intensified winds observed at both TT and PP during El Niño, due to an increased frequency of cold frontal intrusions31 and a southward shift of the Intertropical Convergence Zone (ITCZ)24.Figure Because of its narrow structure and strength, the CAGW plays a dominant role in determining low-level relative vorticity in the EDR, which is a key factor in influencing environmental favorability for tropical cyclogenesis. Figure 35. The southern flank of the PP jet, on the other hand, is characterized by a cyclonic (positive) relative vorticity anomaly. During La Niña, however, the reduced CAGW at TT and PP  basin-wide ENP TC activity during El Niño (La Niña) caused by changes in vertical wind shear, SST, and mid-tropospheric relative humidity is incomplete. The ENP TC response to ENSO is characterized by intrabasin variability, with enhanced TC activity confined to only the WDR and reduced TC activity in the EDR during El Niño, and the opposite during La Niña. Furthermore, this study identifies a topographically locked feature – CAGW– as a primary player in regulating TC activity in the EDR through low-level relative vorticity changes. As all TCs that make landfall onto the Pacific coast of Central America and Mexico form in the EDR, the results presented here have important implications for improving seasonal forecast skill of ENP TCs and their impacts. It points to the necessity of properly resolving and representing the CAGW and its response to ENSO in TC forecast models.7. These types of synoptic CAGW events are especially effective in triggering tropical cyclogenesis when they interact with the monsoon trough37. Understanding synoptic CAGW events as a mechanism of tropical cyclogenesis is an active research area, and more studies are clearly needed to elucidate the underlying dynamical processes and the distinction between their roles in synoptic versus seasonal and longer timescales.We note that the overall reduction of TC activity over the EDR in response to El Niño does not exclude occurrences of individual extreme hurricanes in the region during El Niño. Indeed, Hurricane Patricia in 2015 and Hurricane Pauline in 1997, both among the strongest hurricanes to make landfall over Mexico, occurred during strong El Niño years. Individual hurricane genesis can be initiated by short-lived synoptic events that may not contribute significantly to the mean environment for TC genesis. Hurricane Patricia, for example, appeared to be initiated by a synoptic-scale CAGW strengthening event near TT that provided an injection of cyclonic relative vorticity on the cyclonic shear side and spurred the formation of the initial tropical depressionst through November 30th (hereafter ‘hurricane season’), which accounts for more than 95% (792 out of 832) of the total number of TCs during 1970–2015. Note that our analysis period is slightly different from the ENP hurricane season defined by the National Hurricane Center (NHC), which runs from May 15th through November 30th. Since the number of TCs during our research period covers more than 95% of total number, it is unlikely that the results are sensitive to this difference in hurricane season definition.In this study, all composite and diagnostic analyses focus on the period from June 138 to define ENSO events. The seasonal mean values above the 75th (below the 25th) percentile are chosen as El Niño (La Niña) hurricane seasons. During the period from 1970–2015, 13 El Niño hurricane seasons  and 11 La Niña hurricane seasons  are identified  ×2° (longitude) square box during each hurricane season. To reduce noise and better capture principal anomaly patterns of TC locations, track density is then smoothed by averaging the surrounding eight points. Genesis density has a similar definition, except only the number of tropical cyclogenesis events  in each 2° × 2° square box are counted. Genesis density is also smoothed in the same way as track density.The World Meteorological Organization (WMO) subset of International Best Track Archive for Climate Stewardship (IBTrACS-WMO)40 is also applied to determine the statistical significance level of both genesis and track density. The El Niño composite anomaly is constructed with 13 years randomly chosen from among a total of 46 years. This re-sample process is then repeated 10,000 times to obtain a 95% and 90% confidence interval. The same process is also applied for the La Niña composite anomaly, but by choosing 11 years out of 46-year climatology.In addition to the Student’s t-test, the bootstrap technique22) and its extension, the NCEP Climate Forecast System version 2 (CFSv2)23, are used for TC environmental condition analyses. Both of these datasets are at a high spatial resolution of 0.5° × 0.5°. The CFSR was completed over a 32-year period from January 1979 to March 2011, and then the dataset was extended to the present as CFSv2. To better represent TC environmental conditions, we use 6-hourly rather than monthly mean reanalysis data. 11 El Niño  and 7 La Niña  hurricane seasons are identified during the entire 37-year period from 1979 to 2015 and are used to diagnose TC environmental condition changes during El Niño and La Niña events.To reveal the underlying physical mechanism of intrabasin ENP TC variability, the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR21 (GPI), which is defined as:The environmental favorability for tropical cyclogenesis is assessed by analyzing the genesis potential indexη is absolute vorticity at 850 hPa (s−1), H is relative humidity at 700 hPa (%), Vshear is the magnitude of vertical wind shear between 850 and 200 hPa (m s−1). Vpot is hurricane maximum potential intensity , defined as:TS is SST (K) and To is outflow air temperature at tropopause (K).CP is heat capacity of air,Ck and Cd are the surface exchange coefficients of enthalpy and the drag coefficient (dimensionless), respectively. θ*s and θs are surface saturation equivalent potential temperature and boundary layer equivalent potential temperature (K). The application of PI theory is discussed online (http://wind.mit.edu/~emanuel/holem/node3.html). FORTRAN and MATLAB subroutines are available online (ftp://texmex.mit.edu/pub/emanuel/TCMAX/). To estimate the primary contributions that lead to the ENSO-induced GPI anomalies, the GPI is also recalculated by interannually varying just one term while setting the other three terms to values of the long-term climatology45.where 30. This dataset is at a horizontal resolution of 0.25° × 0.25°, based on an improved Ku-band Geophysical Model Function (GMF) to optimize wind speed retrievals, especially in high wind speed areas. QuikSCAT ocean surface wind is available from 19 July 1999 to 23 November 2009, and is widely used in CAGW observational studies46.The ocean surface wind vector is derived from the National Aeronautics and Space Administration’s (NASA’s) Quick Scatterometer (QuikSCAT) Version-4 (V4) wind productq is specific humidity (kg kg−1), u and v represent the standard horizontal wind components (m s−1), p is air pressure (Pa), and g is gravitational acceleration (m s−2). Therefore qV has the units of kg kg−1 m s−1. Since the units of dp/g, Pa/(m s−2) can equally convert to kg m−2, the term ‘mass weighted’ is used for vertical integration. The vertically-integrated moisture flux is in units of kg m−1 s−1. To convert to a column of water, we assume a constant water density of 103 kg m−3, so the units of the vertically integrated moisture flux can be written as mm m s−1.By vector identity, vertically integrated horizontal moisture flux can be written as:https://rda.ucar.edu/] and National Climatic Data Center (NCDC) repository [https://www.ncdc.noaa.gov/].The datasets generated during and/or analysed during the current study are available in the University Corporation for Atmospheric Research (UCAR) repository [Supplementary Information


These methods were applied to study release of BMAA during acid hydrolysis under a variety of conditions, revealing that the majority of BMAA can be extracted along with only a small proportion of protein. A time course hydrolysis of BMAA from mussel tissue was carried out to assess the recovery of BMAA during sample preparation. The majority of BMAA measured by typical methods was released before a significant proportion of protein was hydrolyzed. Little change was observed in protein hydrolysis beyond typical hydrolysis times but the concentration of BMAA increased linearly. These findings demonstrate protein misincorporation is not the predominant form of BMAA in cycad and shellfish.The non-protein amino acid β-methylamino-L-alanine (BMAA) has been linked to neurodegenerative disease and reported throughout the environment. Proposed mechanisms of bioaccumulation, trophic transfer and chronic toxicity of BMAA rely on the hypothesis of protein misincorporation. Poorly selective methods for BMAA analysis have led to controversy. Here, a recently reported highly selective method for BMAA quantitation using hydrophilic interaction liquid chromatography-differential mobility spectrometry-tandem mass spectrometry (HILIC-DMS-MS/MS) is expanded to include proteinogenic amino acids from hydrolyzed biological samples. For BMAA quantitation, we present a double spiking isotope dilution approach using D BMAA was first identified in the 1960s as a natural product of the cycad plant (Cycas micronesica) during the search for the cause of ALS/PCD on the Pacific island of Guam2. The possibility that BMAA was the cause of ALS/PCD on Guam was later revived by hypotheses that BMAA could be biomagnified through its misincorporation into protein3 and that BMAA was a natural product of cyanobacteria growing symbiotically in the roots of the cycad4. It was also reported that BMAA production by cyanobacteria was not limited to the symbiotic Nostoc sp. in cycad roots but that it was produced in high levels by nearly all species of cyanobacteria investigated5. The validity of these findings5 have since been challenged by researchers in a number of fields including epidemiology6, cycad biology7 and analytical chemistry10.The non-protein amino acid β-methylamino-L-alanine (BMAA) has been implicated in the aetiology of neurodegenerative diseases, particularly amyotrophic lateral sclerosis/Parkinson’s disease complex (ALS/PCD) in humans5. Derivatization chemistry was used to achieve retention of polar BMAA in RPLC and to attach a fluorescent tag enabling detection. This derivatization chemistry has broad specificity for all primary and secondary amino groups and has often been used in combination with single stage mass spectrometry for qualitative confirmation. Concentrations of BMAA as high as 1 g/kg in cyanobacteria5 and 3 g/kg in rodents4 have been reported using RPLC-FLD. Methods have since been developed using tandem mass spectrometry (MS/MS) detection in combination with either RPLC after derivatization16 or hydrophilic interaction liquid chromatography (HILIC) without derivatization21. The detection of g/kg levels of BMAA in biological samples has never been reproduced using these more selective methods, raising concerns about these original reports9. Results of BMAA quantitation using more selective MS/MS methods have been in good agreement in shellfish and diatoms with concentrations reported in the low- to sub- mg/kg. Even using MS/MS methods, inconsistencies in BMAA detection still exist for cyanobacteria and human tissue samples with some labs consistently reporting detection23 and others reporting negative results24.Analysis of BMAA was originally carried out using reverse phase liquid chromatography with fluorescence detection (RPLC-FLD) for quantitation and single stage mass spectrometry (LC-MS) for confirmation of BMAA identity3, sample preparation for BMAA analysis has largely been based on classical methods of strong acid protein hydrolysis. Recently, evidence has been published to suggest that the speciation of BMAA in biological samples is more complex than just “free” and “protein associated” fractions, with a large proportion being present in a third, “soluble bound” fraction26. Rosén et al. carried out a fractionation of low and high molecular weight compounds from neutral extracts of blue mussels and found that bound BMAA was predominantly present in the low molecular weight fraction26. Furthermore, the comparison of hydrolysis of these extracts using strong (6 M HCl) and mild (0.02 M HCl) acid showed that BMAA was released from its bound form under conditions not expected to lead to protein hydrolysis. The presence of a “soluble bound” fraction in cycad, shellfish and BMAA exposed zooplankton was simultaneously reported by an international collaborative study on BMAA analysis25. The fractionation of BMAA can therefore been defined as “free BMAA”, measured by extraction without strong acid hydrolysis, “total BMAA”, measured by total sample hydrolysis or “soluble bound BMAA”, measured by hydrolysis after sample extraction. The speciation of the “soluble bound” fraction remains unknown, and the reliable measurement of BMAA in biological samples remains a challenge.Since the original report of higher recovery of BMAA from biological samples after strong acid hydrolysis27 and another using capillary electrophoresis-MS/MS (CE-MS/MS)28. Both these methods measure un-derivatized BMAA after total sample hydrolysis with limits of detection of 20 μg/kg dry sample. Compared with typical HILIC-MS/MS and RPLC-MS/MS methods used previously in our lab18, both HILIC-DMS-MS/MS and CE-MS/MS methods offer significant improvements in selectivity, limits of detection and confidence of positive identification. In particular, the higher separation resolution of hyphenated HILIC-DMS or CE eliminated interference from isomers and isobaric species, many of which are routinely observed in BMAA analysis27. Excellent quantitative performance has been achieved with both methods using isotope dilution calibration to compensate for matrix effects in ESI. Our work has consistently detected BMAA in shellfish and cycad, but all cyanobacteria samples we have analyzed to date have been negative for BMAA28.Our group has recently reported two highly sensitive and selective new methods for quantitation of BMAA in biological samples, one using HILIC-differential mobility spectrometry-MS/MS (HILIC-DMS-MS/MS)29 and then again later using DMS30. Quantitation of the full suite of un-derivatized proteogenic amino acids in hydrolyzed biological samples has also been shown by ESI-FAIMS-MS/MS using flow injection analysis31.DMS, with planar electrodes, or the similar high field asymmetric waveform ion mobility spectrometry (FAIMS) with concentric cylindrical electrodes, are relatively new gas phase ion mobility separation techniques. Applied to analytical mass spectrometry, DMS acts as an ion filter, separating ions produced by electrospray before they are detected in mass spectrometry. DMS and FAIMS have been used previously as primary separation tools for amino acid analysis by mass spectrometry, but not in combination with liquid chromatography. The separation of leucine and isoleucine, a typical benchmark for ion mobility spectrometry resolution of small molecules, was demonstrated early on in the development of FAIMS as a separation tool for analytical mass spectrometry at the National Research Council Canada27 is expanded to include 17 proteogenic amino acids in order to make it useful in the investigation of the protein bound nature of BMAA in biological samples. We also developed a novel double spiking isotope dilution approach that allowed the study of BMAA extraction efficiency, hydrolytic release and stability in isolation from matrix effects in ESI. Through a variety of fractionations and hydrolysis experiments, these methods were applied to a detailed study of the extraction, fractionation and hydrolytic release of BMAA in shellfish and cycad.Here, the recently reported HILIC-DMS-MS/MS method27. First, two important modifications to this method were required to allow for a detailed study of the extraction, fractionation and hydrolytic release of BMAA. Two different isotopically labelled standards are now available for BMAA; D3-BMAA used in our original studies and 13C15N2-BMAA. It was desirable to develop a method that could selectively measure these two internal standards, each with an [M + H]+ precursor ion of m/z 122, using tandem mass spectrometry. Second, in order to optimize BMAA release and study its relationship to protein hydrolysis, a method suitable for analysis of BMAA and proteinogenic amino acids was desirable.We recently reported the highly selective quantitation of BMAA in cycad and shellfish using HILIC-DMS-MS/MS25, but this approach does not provide any information on the source of the bias. Furthermore, any instability of BMAA and internal standards under hydrolysis conditions would itself introduce a bias on quantitation and free and bound BMAA could be expected to exhibit differing stability under hydrolytic conditions.Several factors can lead to biases in BMAA quantitation including extraction recovery, BMAA stability under hydrolytic conditions and ESI signal suppression from the sample matrix. Fortunately, isotopically labeled standards for BMAA are now readily available and can be used to correct for one or all of these effects, depending on when during the protocol the labeled standard is spiked. A spike added to the initial sample corrects for most possible biases from sample preparation and analysis and is most often used in BMAA quantitation13C15N2-BMAA spiked prior to hydrolysis measured extraction recovery and BMAA degradation. D3-BMAA added after hydrolysis corrected for matrix effects in ESI and additional sample preparation steps such as filtration and allowed for quantitation of degradation of the initial standard spike. The challenge in developing this approach was to achieve selectivity between the two labelled standards, both with the same nominal m/z of 122. Figure 32. From the data shown in Fig. m/z value such as ammonia loss from D3-BMAA at m/z 105 and from 13C15N2-BMAA at m/z 104. A flow injection analysis of the three isotopologues of BMAA was carried out to verify this selectivity and is shown in Fig. 13C15N2-BMAA that can be detected in D3-BMAA transitions.A double spiking isotope dilution protocol was therefore developed to obtain information about both the stability and release of BMAA during hydrolysis, as well as correcting for matrix effects in ESI. Figure 13C15N2-BMAA, hydrolyzed for 12 h at 100 °C, and then spiked with 0.25 nmol D3-BMAA. The use of DMS offers a significant benefit in selectivity and limits of detection compared to analysis of the same mussel tissue RM sample using an equivalent HILIC-MS/MS method without DMS   of acetonitrile are broadly suitable for separation of small polar analytes by FAIMS and DMS, including BMAA and its isomersDV) Fig. . AnalyteDV) Fig. . A gener% of acetThe established DMS-MS/MS parameters for amino acid analysis were combined with the existing HILIC gradient and DMS-MS/MS conditions for BMAA to develop a highly selective multidimensional HILIC-DMS-MS/MS method for BMAA and proteinogenic amino acids. This method is suitable for trace analysis of BMAA and amino acids, but for the intended application of measuring protein hydrolysis in biological samples, a concentration difference between of several orders of magnitude between trace BMAA and protein amino acids made it sub-optimal to measure both in a single run. This was primarily due to the poor HILIC peak shape and detector saturation observed for amino acids at these high concentrations. It was therefore desirable to analyze 500 fold dilutions of hydrolyzed samples in a separate injection for amino acid analysis, as shown in Fig. 37. The relative peak area of these amino acids was compared across different sample preparation and hydrolysis procedures to give a relative measure of the amount of protein hydrolyzed.The goal of the current work was to apply the developed HILIC-DMS-MS/MS methodology to study the hydrolytic release of BMAA and proteinogenic amino acids during strong acid hydrolysis of representative shellfish and cycad samples, while using a cyanobacterial RM negative for BMAA as a control sample. The developed methodology was suitable for measurement of the full suite of proteinogenic amino acids, but not all amino acids liberated from protein are stable to hydrolysis conditions. Based on previous reports of accurate, metrological protein quantitation by hydrolysis and amino acid analysis, proline, valine, phenylalanine, leucine and isoleucine were chosen as the most stable26, but showed a much lower proportion of soluble bound BMAA to free BMAA in cycad seed than reported previously25.Three different sample preparation procedures were investigated: analysis of free BMAA, hydrolyzed soluble BMAA (soluble bound) and total sample hydrolysis without extraction, as summarized in Fig. 26 and repeated here for shellfish and cycad  of the control cyanobacterial RM did not lead to detection of BMAA.Together, these results suggest two different compartments of bound BMAA in mussel tissue, the speciation of each differing significantly from non-specific protein incorporation. The rapid release of BMAA early in the hydrolysis is consistent with the previous suggestion of an unknown, low molecular weight conjugate that releases BMAA under mild hydrolysis conditionsHere we have introduced new methodology that is highly suitable for studying the sample preparation and hydrolytic release of BMAA from biological samples. The double spiking isotope dilution approach for BMAA quantitation allowed BMAA stability during strong acid hydrolysis and ESI matrix effects to be studied independently. This will be of ongoing utility in BMAA method development where it is desirable to examine differences in recovery or stability in isolation from changing matrix effects in ESI. HILIC-DMS-MS/MS is also shown to be well suited to the selective analysis of protein amino acids and the hydrolytic release of stable amino acids is used to study the fractionation of protein and progress of hydrolysis. These methods could equally be applied to help elucidate the speciation of BMAA in other important biological samples such as microalgae and human tissue where BMAA has been reported previously.26. Given that no maximum BMAA concentration from mussels could be observed, even after 5 days of strong acid hydrolysis, the possibility of artefactual formation of BMAA during the hydrolytic reaction should also be considered. It has also been suggested that BMAA could selectively bind to and be incorporated into other biopolymers, specifically the pigment melanin38. It is notable that melanin is also present in shellfish such as the mussels examined here and that the binding of polar neurotoxic paralytic shellfish toxins to melanin has also been previously shown39. However, the low aqueous solubility and high molecular weight of melanin make it an unlikely source of BMAA in the current study. Additional work is required for molecular identification of possible low molecular weight precursor to BMAA as well as to investigate the possibility of its artefactual formation during sample preparation.The results presented clearly demonstrate that BMAA in shellfish and cycad seed is not broadly misincorporated into protein. It is instead present in some other form that appears to include at least two different sources or compartments. The rapid release of BMAA after only 0.5 h of hydrolysis suggests an unidentified, low molecular weight conjugate and is analogous to the recent observation that BMAA was released from mussels under milder acidic conditions3-BMAA was initially synthesized in-house, as described previously27 and later purchased from Abraxis LLC . 13C15N2-BMAA dihydrochloride was purchased from Isoscience . The structure, purity and concentration of BMAA and internal standards was verified by 1H nuclear magnetic resonance spectroscopy (NMR)40. NMR stock solutions were diluted to 10 µM for BMAA and 25 µM for the internal standards and aliquoted into argon purged, flame sealed ampoules for use as stock solutions to prepare calibration standards.Optima LC-MS grade acetonitrile and a mixed L-amino acid standard  were purchased from Thermo Fisher Scientific . Formic acid (>98% ACS grade) was purchased from Sigma Aldrich . β-N-Methylamino-L-alanine hydrochloride was obtained from Tocris Bioscience . DCycas thouarsii were obtained from rarepalmseeds.com  and the endosperm of one seed was homogenized in a ball mill for 30 min, freeze-dried, and ground in a mortar and pestle. A steamed lobster (Homarus americanus) sample was purchased from a local supermarket . Muscle tissue from the legs and tail were homogenized in a blender, freeze dried, and ground by mortar and pestle. A mussel (Mytilus edulis) tissue RM certified for several marine algal biotoxins (CRM-FDMT) was acquired from the National Research Council Canada 44. A recently developed pilot scale cyanobacterial RM that has been extensively characterized for a wide range of cyanotoxins was used as a negative control for BMAA45.Seeds of 27. Triplicate samples of 50 mg freeze-dried tissue were weighed into 5 mL amber glass ampoules with 2 mL 6 M HCl, spiked with 100 µL of 2.5 µM 13C15N2-BMAA and purged with argon before flame sealing. Hydrolysis was carried out in an oven at 110 °C for 15 h, unless otherwise specified. After hydrolysis, samples were spiked with 100 µL of 2.5 µM D3-BMAA, evaporated to dryness at 60 °C under nitrogen, reconstituted in 1 mL of 2 mM HCl, and filtered to 0.22 μm using a Millipore Ultrafree-MC spin filter. The soluble fraction hydrolysis procedure was adapted from Reveillon et al19. Triplicate samples of 50 mg freeze-dried tissue were weighed into 5 mL reaction vials with 0.5 g of 75 μm acid washed glass beads  and 2 mL of 0.1 M trichloroacetic acid (TCA), spiked with 100 µL of 2.5 µM 13C15N2-BMAA and then shaken at 30 Hz for 30 min. Samples were centrifuged at 3100 × g and 15 °C for 10 min. Supernatant was transferred to a 5 mL amber ampoule and the extraction was repeated with an additional 2 mL of 0.1 M TCA. The pooled extract was either analyzed directly to measure free BMAA or was evaporated to dryness at 60 °C with a gentle stream of nitrogen and hydrolysed using the same conditions used in the total extraction prior to analysis. These sample preparation workflows are summarized graphically in Fig. Two different methods were used for sample hydrolysis: A total tissue hydrolysis and a soluble fraction hydrolysis. The total tissue hydrolysis procedure was modified from our previous reportFor analysis of protein amino acids, a 500 fold sequential dilutions of sample hydrolysates in water were carried out using a Gilson Aspec GX 271 liquid handler .−1. A linear gradient ran from 10 to 35% A over 15 min followed by a 6 min isocratic period, a linear gradient to 45% A over 1 min, an 8 min isocratic period, a 5 min column flush at 90% A and a 10 min equilibration at 10% A27.LC separation was performed using a 5 μm TSKgel Amide-80 column (250 mm × 2 mm i.d.)  held at 40 °C and a mobile phase of 50 mM formic acid in both water (A) or 95% acetonitrile (B) at a flow rate of 300 µL min27. Turbospray parameters included a spray voltage of + 5500 V, curtain gas of 20 psi N2, collision gas of 5 psi N2, desolvation gases of 45 psi (GS1) and 50 psi (GS2) N2, and a spray temperature of 400 °C. Mass spectrometer settings included a declustering potential of 140 V, an entrance potential of 10 V and exit potential of 13 V, DMS settings included separation (dispersion) voltage of 2600 V, a carrier gas modifier of 0.35% acetonitrile, a DMS temperature of 150 °C, and a DMS offset of −3 V.Detection was carried out using an AB Sciex  QTRAP 5500 mass spectrometer equipped with a Turbospray ionization source and SelexION differential mobility spectrometer. The DMS carrier gas modifier solvent delivery system was adapted, as described previously, to allow for delivery of a full range of modifier concentrations and better solvent evaporation and mixing−1 into a 350 µL min−1 flow of 1:1 MeCN:H2O with 50 mM formic acid and collecting compensation voltage scans using selected reaction monitoring (SRM) with the transitions for each amino acid reported previously46. The concentration of acetonitrile in the N2 carrier gas was varied over a range of 0.04 to 2.5% and separation voltage was varied over a range from 2000 V to 4000 V. Optimized retention times, SRM transitions, collision energy, and DMS compensation voltages used for sample analysis are listed in Table DMS conditions for each amino acid were optimized by infusing the diluted amino acid standard at 10 µL minSupplementary information


Juvenile idiopathic arthritis (JIA) is a rare disease that is not widely known by paediatricians and general practitioner (GP) leading to diagnostic error and delayed care provision. We aimed to analyse patient’s journey and time to diagnosis of JIA (delay from the first symptom to the diagnosis of JIA).We performed a retrospective cohort study of 67 patients diagnosed with JIA and seen in the paediatric rheumatology department of the Kremlin Bicêtre Hospital, between July 2002 and January 2015. Patients were selected for analysis in order to represent an equal distribution of five JIA subtypes: oligoarticular onset (21), polyarticular onset (13), enthesitis-related arthritis (17), and systemic onset (16).n = 9), ERA (n = 7), OAJIA (3) and POJIA (n = 6) for whom diagnosis was suspected straightaway. In most cases (88%), JIA was established by paediatric rheumatologists.Sixty-seven patients were finally analysed (42 girls). Before JIA diagnosis was made, patients had visited a mean of three physicians ). Emergency room physicians (52%) were the first patient’s referral before GP (42%). Paediatric rheumatologists were mostly seen as third referral . Reactive arthritis (34%) and septic arthritis (24%) represented both the most common initial diagnosis. JIA was suspected after an average median time delay of 3 months (0.26–81.2) except for 25 patients (37%): SJIA . Paediatric rheumatologist played a major role in making the diagnosis but the journey to reach them was long and complex with multiple referrals. These results reinforce the necessity of improving GP and emergency physician’s awareness and education on paediatric rheumatic diseases as the importance of a strong network in paediatric rheumatology to improve patient’s level of care.We highlighted the complex patient’s journey to diagnosis in children with JIA and made assumptions that reference center might reduce time to diagnosis although not statically proven. Further analysis with a larger number of patients might be needed to better investigate this probability. Juvenile idiopathic arthritis, JIA, is the most frequent cause of inflammatory arthritis in children before 16 years. Even if considered a rare disease, it’s estimated incidence rate is different around the world with low incidence in Asian population and relatively higher incidence in those of European descent  . In contWe performed a retrospective cohort study of patients diagnosed with JIA according to the ILAR criteria and seen in the paediatric rheumatology center of Kremlin Bicêtre, a single tertiary and reference center for paediatric rheumatology in France, between July 2002 and January 2015. Patients were randomly selected for analysis and classified in five JIA subtypes: e.g. oligoarticular onset (OAJIA), oligo-onset (persistent and extended) polyarticular onset (POJIA) (rheumatoid factor (RF) positive and negative), enthesitis-related arthritis (ERA), and systemic onset (SoJIA). In addition, sufficient information on patient’s journey to diagnosis and care was required.We collected demographic clinical and biological information , RF and HLA-B27) where available. We recorded also all major medical investigations and referrals, treatments and differential diagnoses made before diagnosis confirmation. The time to diagnosis was defined as the delay from the first symptom to the diagnosis of JIA. According to our national regulations, no IRB approval was required.The cohort’s characteristics, time to diagnosis, and other variables were analysed using descriptive statistics. Total time to diagnosis was secondarily adjusted on sex, age and number of symptoms at disease onset, type of JIA, first referral physician consulted and the distance between home and reference center using a multivariate logistic regression.Sixty-seven patients were finally analysed : 21 were diagnosed with OAJIA, 16 with SoJIA, 17 with ERA and 13 with POJIA. Mean age at disease onset was of 6.4 ± 4.6 years  (0.5–15.6). The whole population characteristics are summarized in Table n = 9), ERA (n = 7), OAJIA (3) and POJIA (n = 6) for whom diagnosis was suspected straightaway , arthritis 25%), and fever 18%) followed by skin rash (8%), limping (9%), abdominal pain (1.3%), and uveitis (1.3%). Before JIA diagnosis was made, patients had visited a mean of three physicians ). Emergency room physicians (52%) were the first patient’s referral before the general practitioner (42%) . Age at disease onset was of 6.4 ± 2.5 years  (0.4–15.2) and initial symptoms included fever 81%, skin rash 37.5%, and arthralgia 31%  started their disease at 3.6 ± 2.9 years  (1.08-11.6). Arthritis (62%) and arthralgia (24%) were the main presenting symptoms , started their disease at 5.7 ± 4.2 years  0.9–13). Arthralgia (77%) and arthritis (15.4%) were the main presenting symptoms  started their disease at 10.4 ± 4.2 years  (1.5–15.6). Initial symptoms were mostly arthralgia (59%), arthritis (17.6%) and limping  Fig. . Septic This study analyses a representative cohort of JIA patients affected by four main JIA subtypes . SurprisPaediatric rheumatologist played a major role in making the diagnosis but the journey to reach them was long (6 months on average) and complex with multiple referrals (99%), unjustified diagnostic procedures and inappropriate diagnoses , 14. SimOur study represents a first attempt to determine the level of wandering in JIA diagnosis in a country which has been the first to increase the visibility of care for rare diseases by creating reference centres. Although the distance between home and the reference center was not found to correlate with time to diagnosis, we made assumptions that it could be one reason for rather earlier referral than previously reported in other Western countries; indeed, three-fourths of patients referred to us for JIA are living in Paris and the “Ile de France” region. An analysis with larger number of patients might be needed to better investigate this probability. Nevertheless, other factors could play a key role in reducing time to diagnosis such as elevated ESR, type of JIA and presence of enthesitis. Larger studies are needed to evaluate these parameters. However, the apparent limited median delay to diagnosis observed herein must be dampened by the wide ranges, up to 86 months in POJIA. In addition, part of the collection of data was retrospective including somewhat recall biases.In conclusion, we have highlighted the complex patient’s journey to diagnosis in JIA, possibly improved by our reference center effect although no significant correlation was found. The limited number of patients presented calls for a nationwide survey.


The experimentally observed phase transition sequence nematic (N) N + 6 two-dimensional hexagonal (2D-H) is in good agreement with the theoretical predictions. Further, the present study also brings to light the effect of chirality on the N + 6 phase. In the chiral N + 6 phase the bond-orientational order within each “polymer” bundle is found to be twisted about an axis parallel to the average polymer direction. This structure is consistent with the theoretically envisaged Moiré state, thereby providing the first experimental demonstration of the Moiré structure. In addition to confirming the predictions of fundamental theories of two-dimensional melting, these results are relevant in a variety of situations in chemistry, physics and biology, where parallel packing of polymer-like objects are encountered.We report the discovery of a thermodynamically stable line hexatic (N + 6) phase in a three-dimensional (3D) system made up of self-assembled  The occurrence of the hexatic phase was first proposed in the context of melting of two-dimensional 2D) crystals, as an intermediate phase between the crystalline and liquid phases1D crystal14line-hexatic or N + 6 phase since nematic order coexists with BO in the plane normal to Unlike their 2D counterparts, three-dimensional (3D) crystals melt directly into the liquid phase via a first-order transition. The exception however being 3D crystals made up of oriented polymer-like constituents where the possible presence of an intermediate hexatic phase has been theoretically demonstratedAlthough the N + 6 phase has been theoretically predicted to occur as an intermediate phase between the N and the 2D-H phases, this is not the case in the two systems where this phase has been experimentally reported until now. In both these systems the N + 6 phase arises due to packing frustrations imposed by the shape of the individual constituents, and occurs close to their highest concentration compatible with 2D packing.Occurrence of the N + 6 phase in 3D systems was first experimentally reported in dense aqueous solutions of long DNA fragments7In the other instance, occurrence of the N + 6 phase was reported in dense suspensions of thin hard colloidal discs that stack into long columnsMoiré phase, consisting of braided bundles of polymers, with BO in each bundle twisted about an axis parallel to the average polymer direction; in this phase the twist axis is parallel to Influence of molecular chirality on the structure of the N + 6 phase has also been theoretically investigated141531718thermodynamically stable line-hexatic phase formed by self-assembled polymer-like micelles made out of a mixture of an amphiphile, sodium dodecylsulphate (SDS), and organic salt, p-toluidine hydrochloride (PTHC) ; (b) chiral analogue of N + 6 phase; and (c) the observation of the theoretically predicted N In this article we report the discovery of (a) a perpendicular geometry, where the incident x-ray beam is normal to q⊥, indicating that the cylindrical micelles have long-range orientational order along z. The position of the peak gives the average lateral separation between the micelles, while its width is inversely proportional to the translational correlation length ξ in the medium. The intensity profiles at different temperatures  patterns obtained using samples in the eratures , reveal tructure .schlieren texture in the POM micrograph which is characteristic of the N phase . Micrographs obtained at different temperatures are shown in  N phase . On heat N phase , no indiperature  can be aparallel geometry with the incident x-ray beam parallel to q⊥ plane. In contrast, long-range BO in the high temperature (50 °C) 2D-H phase gives rise to six sharp spots in the q⊥ plane  phase develops only after about 10 hours, presumably due to the very high viscosity of these samples. Two transitions, indicated by abrupt changes in the texture, are seen at around 33 °C and 40 °C on heating; which correspond closely to the boundaries of the region highlighted in ξ varies strongly with temperature. These transitions are reversible on cooling. SAXS peak width of the chiral sample shows identical temperature dependence as that of the achiral sample  and the total surfactant weight fraction of 0.5 (SDS + PTHC)/(SDS + PTHC + water) = 0.5)30Sodium dodecylsulphate (SDS) (>99% purity) and p-toluidine hydrochloride (PTHC) (98% purity) were obtained from Sigma-Aldrich. Experiments were performed at a PTHC to SDS molar ratio of 0.1  provided with a heating or cooling stage (Mettler FP82HT) and a central processor (Mettler FP90). Appropriate amount of samples were taken between a glass microscope slide and a glass coverslip. They were then placed inside the temperature-controlled chamber (heating or cooling rate 1 °C/min) and observed between crossed polarizers. The temperature of each sample was varied from 25 to 60 °C.−1. Temperature stability was better than 0.1 °C. Samples for SAXS studies were taken in sealed glass capillaries. All the samples were initially aligned in the nematic phase and the alignment was found to be retained on heating to the higher temperature phases. Orientation of the average micellar axis, i.e. the nematic director SAXS experiments were carried out using a Hecus SAXS-Eye system, in conjunction with either a CCD detector or a position sensitive detector. Details about the experimental set up and data acquisition have been described quite elaborately elsewhereHow to cite this article: Pal, A. et al. Observation of the Chiral and Achiral Hexatic Phases of Self-assembled Micellar polymers. Sci. Rep.6, 32313; doi: 10.1038/srep32313 (2016).


Different cell types exhibit distinct patterns of 3D genome organization that correlate with changes in gene expression in tissue and differentiation systems. Several tissue-specific nuclear envelope transmembrane proteins (NETs) have been found to influence the spatial positioning of genes and chromosomes that normally occurs during tissue differentiation. Here we study 3 such NETs: NET29, NET39, and NET47, which are expressed preferentially in fat, muscle and liver, respectively. We found that even when exogenously expressed in a heterologous system they can specify particular genome organization patterns and alter gene expression. Each NET affected largely different subsets of genes. Notably, the liver-specific NET47 upregulated many genes in HT1080 fibroblast cells that are normally upregulated in hepatogenesis, showing that tissue-specific NETs can favor expression patterns associated with the tissue where the NET is normally expressed. Similarly, global profiling of peripheral chromatin after exogenous expression of these NETs using lamin B1 DamID revealed that each NET affected the nuclear positioning of distinct sets of genomic regions with a significant tissue-specific component. Thus NET influences on genome organization can contribute to gene expression changes associated with differentiation even in the absence of other factors and overt cellular differentiation changes. The nuclear envelope (NE) contributes significantly to the 3D spatial organization of the genome.There is no clear consensus on the general question of the relationship between gene position and expression. Some data argues that repositioning drives changes in expressionThe recent identification of several tissue-specific NETs that direct chromosome and gene positioningTo determine if the observed changes in gene positioning or expression depended on differentiation, we tested whether the tissue-specific NETs could direct these changes in a heterologous system. Previously we demonstrated that expression of several tissue-specific NETs could promote chromosome repositioning to the NE in heterologous HT1080 fibroblast cancer cells.We tested whether the NET-induced chromosome repositioning was accompanied by gene regulation changes in the heterologous HT1080 fibroblasts where these NETs are not normally expressed. RNA was prepared from 3 separate passages of HT1080 lines stably expressing GFP-NETs and analyzed on Illumina bead microarrays. NETs 29, 39, and 47 were respectively expressed 2.5, 4.3, and 3.6-fold over endogenous levels by semi-quantitative RT-PCR. Compared to the NLS-GFP control each NET yielded a distinct pattern of overlapping and unique changes in gene expression  analysis revealed a striking enrichment of genes involved in tissue remodeling, differentiation and proliferation compared with the genome as a whole (i.e. red spots appearing above the dotted 2-fold upregulation line. The visible trend for more upregulated genes in differentiation matching with genes upregulated in the NET47 HT1080 data sets was further supported by the probability of achieving this distribution randomly being only 8% (Kolmogorov-Smirnov (KS) test), which is remarkable considering that the HT1080 fibrosarcoma cells likely express few, if any, liver-specific accessory factors. Notably the genes involved in hepatic differentiation had virtually no overlap with those affected by the soluble fragments (Supplementary Table S1A). The genes affected tended to be important for hepatic differentiation and liver function. The importance of collagen (COL15A1) and acyl-coenzyme A synthetase (ACSL5) are obvious for liver function. TGF-β signaling (TGFBR3), arrestin β (ARRB1), kallikrein peptidase (KLK6), procollagen C-proteinase enhancer protein (PCOLCE), and matrilin (MATN2) are all important for liver differentiation and/or regeneration.As NET47 knockout mice exhibited loss of expression of several liver genes,CYBRD1), peptidyl-prolyl isomerase C (PPIC) and tryptophan 2,3-dioxygenase (TDO2) or liver differentiation such as the T-box transcription factor TBX3.The overlap between genes upregulated during hepatic differentiation and genes upregulated due to NET overexpression was only observed for the liver-specific NET47, and not for NET39 (muscle) or NET29 (fat). Interestingly, for NET39 the overlap between genes differentially expressed and those upregulated in hepatic differentiation strongly highlighted genes that were downregulated by the overexpression of the NET . Again many of the most affected genes are notably important for liver function such as cytochrome B  ratios were generated for the numbers of sequencing reads across the genome and plotted to identify lamina-associated domains (LADs) at the nuclear periphery. This ratio represents, in essence, the likelihood that a particular region is associated with the NE averaged across the whole sample cell population over 2–3 cell divisions. An example DamID trace is shown in ng cells . These rPlotting the relative intensities along the trace as a heatmap revealed additional subtle differences between the NETs in their effects on peripherally associated genome regions , bottom.To facilitate comparison of LADs between conditions, we classified the LADs into clusters of overlapping LADs across conditions, as their boundaries rarely exactly coincide between conditions. Just as gene expression effects exhibited considerable specificity for each NET , a similWhen the specificity of these PI and IP regions was graphed, again the number of changing regions was greater for those specific to individual NETs than changing regions shared by all NETs . Unlike i.e., IP genes were downregulated when associated with the periphery while PI genes were upregulated upon release .−04 and 0.06 respectively). For NET29 there were only 50% genes changing position and expression in the expected direction (Fisher's test p < 0.28). The scatterplots show the laminB1-DamID signal plotted against the expression changes  and had altered expression did so in the expected direction  changes . Upreguli.e., downregulated genes that move to the periphery. A similar result was observed for upregulated genes, being more likely to be released from the periphery, except for NET47 possibly due to the low number of changing genes observed. It is interesting that in each case, it is the downregulation/IP association that seems strongest. It is possible that this is a reflection of the nature of the heterologous system in that it probably lacks the relevant tissue-specific transcription factors to activate genes once they move away from the repressive environment of the NE, while as a general property of the nuclear periphery repression may require fewer or no tissue-specific factors.There was a much higher proportion of genes exhibiting changes in the opposite direction than observed previously in the muscle differentiation system.in vitro myogenesis.NET39 is a muscle-specific NET that influences gene positioning and expression in myogenesis;PPARG locus, in control HT1080 cells there is normally a small LAD covering the promoter and 50–60 Kb upstream from it, while the body of the gene is in a long stretch devoid of DamID signal (PPARG is strongly upregulated (Supplementary Table S1A).The transcription factor PPARγ is well known as a master regulator of adipogenesis;D signal . Upon ovNET39 and other muscle-specific NETs recruit critical myogenic genes to the nuclear periphery during muscle differentiation, thus adding roughly 1/3–2/3 of their normal repression; however, ectopic expression of these NETs in myoblasts was still able to reposition the genes but without corresponding changes in gene expression.FBLN1,KLK6,TGFBR3,NDRG2,PCOLCE,ACSL5.KLK6,MATN2,HSPB8TDO2 that is regulated by bone morphogenic trancsription factors in liver injury,TBX3 that has its levels altered at multiple stages in liver differentiation,ENDOD1 that is associated with metastasis,NNMT that needs to be tightly regulated or else it can yield obesity.Although fewer genes were regulated by NETs in the HT1080 cells, these genes were typically those that require ‘tighter’ regulation in their natural context. When genes upregulated by NET47 in the HT1080 cells were compared with genes normally upregulated in hepatogenesis, the overlapping set included several for which the levels are altered in hepatocellular carcinoma or other liver diseases such as non-alcoholic steatohepatitis: MyoD, Myf5 and Pax7.Cyp3 and IgH loci in fibroblasts.While there are many possibilities for what contributes the gene regulation in these cases, one stands out due to previous links with NE-directed gene regulation: the addition of silencing marks once at the periphery. Silencing enzymes such as HDAC3 are recruited to the periphery by the ubiquitously expressed NETs LAP2ß and emerin.PPARG upregulation with exogenous NET39 expression. PPARγ is an important transcriptional driver for adipogenesis but it also plays a role in myogenesis, where critical expression of PPARG is necessary for early differentiation of skeletal muscle cells: altered expression inhibits myogenesis.PPARG gene was mostly in an inter-LAD position, but it clearly repositioned toward the periphery in the muscle-specific NET39-expressing HT1080 line. There was a strong increase in lamin B1-DamID signal in the middle of the gene and upstream of the promoter; however this repositioning was associated with a shift that made the promoter slightly more accessible, with a window of ∼30 Kb showing no peripheral association. In C2C12 myogenesis PPARG was both downregulated and repositioned to the periphery.PPARG to the periphery, and, second, its upregulation. As a result, the small LAD just upstream of PPARG extends to include most of the gene, except for a ∼30 Kb window around the promoter. It is unclear whether this is because the cells are maintained in an ‘early differentiation’ like state, where the switch to silencing has not yet occurred and the gene is positioned in an environment conducive to quick and permanent silencing, or perhaps the switch is ineffective because the HT1080 cells do not express myoblast-specific factors.This was likely the case for the This specific example of a gene that is strongly upregulated while actually increasing its peripheral association shows that the reported gene activation driving release from the peripheryThese data contribute to our understanding of the NE's role as an exciting additional layer of genome regulation. Multiple mechanisms can function to regulate gene expression associated with gene repositioning. Nonetheless, while the partial overlaps between the specific genes repositioned and regulated by NET39 in myogenesis and in the HT1080 fibroblasts indicate that the NETs alone contribute considerably to this mechanism, at the same time the fact that many more tissue-specific genes were affected in the tissue differentiation system argues that such questions are best addressed using actual tissues or differentiation systems. Tissue-specific NETs are clearly involved in genome organizationNET-GFP fusions have been previously describedHuman HT1080 fibroblasts and derivatives stably expressing NETs were maintained in high glucose DMEM supplemented with 10% fetal bovine serum (FBS), 100 µg/ml penicillin and 100 µg/ml streptomycin sulfate. HT1080 cells were stably transfected using linearized plasmids carrying NET-GFP fusions. Transfectants were initially selected for with 500 µg/ml Geneticin for 2 weeks and surviving cells were further enriched for those expressing the GFP fusions by FACS. Cells were maintained thereafter with 100 µg/ml Geneticin.Total RNA from cells stably transfected with NET-GFP fusions and from controls (transfected with NLS-GFP and untransfected) was extracted with TRIzol Reagent  according to the manufacturer's instructions. The RNA was converted to cRNA and labeled with biotin using the Illumina TotalPrep RNA Amplification Kit . For each analysis, at least 3 biological replicates were hybridized to Illumina whole genome gene expression arrays (HumanHT-12 BeadChip v3). These arrays have a coverage of 48,803 transcripts representing 18,187 RefSeq genes (HG19).Hybridizations were performed by the Wellcome Trust Clinical Research Facility associated with the University of Edinburgh, using an Illumina Beadstation. Microarray data were quantile normalized and analyzed in the R environment using the Bioconductor package Limma5 cells.Lentiviruses encoding DamID constructs were generated as described in5 HT1080 cells each, and 24 h later they were transduced with 5–10 µl of a Dam methylase encoding lentiviral preparation in the presence of 6 µg/ml polybrene. After 72 h cells were trypsinized, pelleted at 1,000 x g for 2 min and DNA extracted. DamID sample processing was then performed as described in Vogel et al. Briefly, DNA was extracted from cells using the DNeasy tissue lysis kit  as per manufacturer's instructions. 2.5 µg of extracted DNA was then digested by DpnI (NEB) and, following heat inactivation of DpnI, was ligated to the DamID adaptor duplex (dsAdR) generated from the oligonucleotides AdRt (5′-CTAATACGACTCACATAGGGCAGCGTGGTCGCGGCCGA-GGA-3′) and AdRb (5′-TCCTCGGCCG-3′) after which DNA was further digested by DpnII. To amplify DNA sequences methylated by the Dam methylase, 5 µl of DpnII digested material was then subjected to PCR in the supplied buffer in the presence of the 1.25 µM Adr-PCR primer (5′-GGTCGCGGCCGAGGATC-3′), 0.2 mM dNTPs and 1X of the Advantage cDNA polymerase . PCR was performed with 1 cycle at 68°C for 10 min followed by 1 cycle of 94°C for 3 min, 65°C for 5 min and 68°C for 15 min, then followed by 4 cycles of 94°C for 1 min, 65°C for 1 min and 68°C for 10 min, and finally followed by 17 cycles of 94°C for 1 min, 65°C for 1 min and 68°C for 2 min. Following PCR, the distribution of amplified DNA fragments was checked on agarose gels and purified on QIAquick PCR purification columns  and then concentrated to the required concentration by precipitation. To generate the 2 µg of material required of next generation sequencing it was found an average of 6–8 PCR reactions were required per sample.DamID was performed as described in.https://www.R-project.org/) and Bedtools.DamID sample libraries were prepared for next generation sequencing by fragmentation followed by ligation to sequencing adaptors. DamID sequences (GEO accession GSE87228) were aligned to the human Hg19 genome using the Burrows-Wheeler Aligner software bwa-mem.DNAcopy: DNA copy number data analysis. R package version 1.46.0) using the default parameters. The positive signal tracts were extracted and merged if they were <5 Kb apart. We removed anything below 15 Kb from our LAD list. This threshold was chosen empirically after careful examination of the LAD traces. We considered a gene being in a LAD if it at least overlapped with one.To identify LADs we used a circular binary segmentation (CBS) algorithm in the Bioconductor package DNAcopy (Seshan VE and Olshen A (2016). To identify genomic regions with differential frequencies of association with the periphery between WT HT1080 cells and HT1080 cells stably expressing NETs, we used essentially the method we described in Robson et al.Regions that experienced an increase in signal were termed IP, representing a shift from the interior toward the periphery, while regions that experienced a decrease in signal were termed PI and represented a shift away from the periphery. Genes that overlapped IP or PI regions were referred to as IP or PI genes respectively.Genes differentially expressed in HT1080 and NET-expressing HT1080 cells were analyzed for Biological Process and Cellular Compartment GO-term enrichment using Gene Ontology enrichment analysis and visualization tool GOrilla.For Supplementary Table S3 in addition to the gene set listings there is also a transcription factor analysis performed using EnrichR.


Thalassiosira pseudonana in mid-20th century (300 ppm CO2) and future (1000 ppm CO2) conditions that cause ocean acidification, using a stress test that probes its ability to recover from incrementally higher amount of low-dose ultraviolet A (UVA) and B (UVB) radiation and re-initiate growth in day–night cycles, limited by nitrogen. While all cultures eventually collapse, those growing at 300 ppm CO2 succumb sooner. The underlying mechanism for collapse appears to be a system failure resulting from “loss of relational resilience,” that is, inability to adopt physiological states matched to N-availability and phase of the diurnal cycle. Importantly, under elevated CO2 conditions diatoms sustain relational resilience over a longer timeframe, demonstrating increased resilience to future acidified ocean conditions. This stress test framework can be extended to evaluate and predict how various climate change associated stressors may impact microbial community resilience.The fate of diatoms in future acidified oceans could have dramatic implications on marine ecosystems, because they account for ~40% of marine primary production. Here, we quantify resilience of  Diatoms account for 40% of marine primary production and their sensitivity to ocean acidification could have ecosystem-wide consequences. Here, the authors developed and applied a stress test, demonstrating that resilience of diatoms increases significantly in ocean acidification conditions. For instance, coccolithophores are predicted to become more sensitive to ocean acidification4, because it will synergistically exacerbate their susceptibility to other stressors such as ultraviolet radiation (UVR)5. However, the intricacies of elevated CO2 on marine carbon chemistry and its effect on coccolithophores have yielded varied results6 and highlights the complexity of ocean dynamics. Ocean acidification is also predicted to cause a decline in the bioavailability of iron (Fe), thereby imposing additional stress on phytoplankton populations7.By the end of the twenty-first century atmospheric CO8, diatoms are a vital base for the food chain and the biological carbon pump—a complex set of interactions among diverse microorganisms that transports fixed carbon from surface phototrophic zones to the deep ocean9. Although species composition and abundance of diatoms are known to fluctuate with environmental changes, their fate in acidified oceans of the future is uncertain13. Thus, diatoms are an integral group for monitoring environmental conditions. They are known to have been impacted by prior climate shifts and have been used as record keepers of Earth’s past conditions14. For example, species composition and isotopic signatures of diatom microfossils have been used to infer nutrient conditions during the last ice age15 and trace how biological carbon export production changed throughout the glacial and interglacial cycles16. Environmental histories can be inferred using simple transfer functions that correlate diatom sensitivity to specific factors such as CO2 levels17, sea surface temperatures18, upwellings, eutrophication events20, and even dynamics of ocean currents21. However, it is complicated to predict how diatoms will respond to future climates by simply correlating the consequence of changing one or a few environmental conditions on growth. Moreover, improved growth rate22 or increased biomass accumulation under higher CO2 conditions does not necessarily mean in itself that diatoms will be less sensitive to ocean acidification, that is, more stable.As dominant primary producers in marine ecosystems26. The more resilient a system, the larger is the disturbance needed to force it into an alternate stable state27. We developed a stress test to quantify resilience of diatoms under simulated mid-twentieth century and future oceanic conditions, by assaying their ability to tolerate and recover from progressively larger amounts of stress. The primary objective of the stress test was to investigate whether growth under elevated CO2 would alter diatom resilience. For instance, elevated CO2 reduces the need for biophysical carbon concentrating mechanisms (CCMs) to saturate RuBisCO  at approximately 80%, while minimizing diffusion of CO2 back across membranes34. When ambient CO2 doubles, it is estimated that the resulting downregulation of CCMs conserves 3–6% of the energy required for carbon fixation in diatoms28. We hypothesize that the predicted energy savings during growth under elevated CO2 could be reallocated for state transitions or potential stress management and thereby improve the resilience of diatoms in future oceanic conditions.The concept of “ecological resilience” may be a more apt metric of stability and is defined as “the amount of disturbance that can be tolerated by a system without changing state and still persist”Thalassiosira pseudonana has evolved in a dynamic environment experiencing daily and seasonal changes with both predictable and unpredictable fluctuations in diverse environmental factors including light, pH, temperature, salinity, and micronutrient availability. Accordingly, T. pseudonana can adopt at least four principal physiologic states matched to four key environmental conditions , and it possesses regulatory networks to mediate transitions between these states35. Energetically expensive mechanisms  are required to both sustain an environmentally relevant physiological state in face of small perturbations and to drive transition to a new state in response to, or in anticipation of36, an environmental change35. When faced with a fluctuating environment, the success of an organism depends on its ability to efficiently manage trade-offs between allocating resources for producing biomass and transitioning between alternate physiological states, while mitigating consequences of the associated stress38. We speculated that within such a fluctuating environmental framework, any stabilizing or destabilizing effect of ocean acidification on the diatom T. pseudonana should be detectable in terms of altered dynamics of its capacity to re-establish growth from incrementally increasing stress39, and its subsequent ability to restore and maintain routine transitions across the aforementioned four physiologic states.The diatom T. pseudonana in mid-twentieth century CO2 conditions  and projected end-of-twenty-first century conditions , while transitioning between the routine fluctuations of four physiological states . Culturing in nitrogen-limiting conditions imposes an added requirement that diatoms shift from assimilating externally available nitrate in early phases of growth to recycling internal nitrogen reserves at later stages when they reach carrying capacity40. In addition to deceleration in growth rate, this shift is accompanied with a reduction in photosynthetic efficiency41, thereby requiring coordination across diurnally and nutritionally modulated physiological states35. Thus, we speculated that the energetically expensive acclimation to continually fluctuating environments might manifest in differences in response and recovery dynamics between the LC and HC cultures.We investigated the stability and the response and recovery dynamics of Thalassiosira pseudonana was batch cultured in triplicate photo-bioreactors with nitrogen-limiting conditions (~65 μM nitrate), 12:12 h light:dark (L:D) cycles, and saturating photon flux density (275–300 μmol photons m−2 s−1). At the end of each growth cycle or “stage” ), a small culture aliquot was transferred into fresh nutrient replete medium to re-initiate growth . Exposure to UVR in the photic zone can damage photosystem II (PSII) and inhibit photosynthesis in phytoplankton49. UVR also inflicts molecular and cellular damage50 directly through the formation of cyclobutane pyrimidine dimers in DNA47 and indirectly through generation of reactive oxygen species (ROS)48. The combined effects of elevated CO2 and UVR are complex and directional, whereas acclimation to UVR reduces susceptibility to photoinhibition of diatoms at high and low CO2 conditions; acclimation to elevated CO2 has been shown to increase their sensitivity to photoinhibitory UVR46. In the first stage of the stress test, diatom cultures did not receive any UVR, but in subsequent stages, each culture was subjected to an incrementally higher dose of UVR (0.5 mW cm−2) for 1 h in the middle of the light cycle   Fig. . Under b−2) Fig.  and comp2 conditions to investigate if differential gene expression would yield a mechanistic explanation for why low doses of UVR in conjunction with periodic physiological state transitions drives diatom cultures under LC conditions towards collapse sooner than cultures growing in HC conditions. The transcriptome sampling schedule captured transitions of the diatom cultures across the four physiologic states. We performed targeted analysis of the transcript level changes in genes that are putatively associated with UVR-generated stress and carbon metabolism. We analyzed transcript levels of 38 putative oxidative stress response (OSR) genes  that are known to mitigate cellular damage caused by ROS generated by UVR exposure , which has been reported to be expressed only when CO2 is limited, and speculated to play a wider role in how diatoms respond to CO233  were significantly downregulated under HC conditions . The downregulated genes included bestrophin-like proteins, which share homology with a family of anion-selective channels53 permeable to bicarbonate54, as well as carbonic anhydrases34  mapped to the four corners of this 2D state space, representing the four physiological states: light (early and late) and dark (early and late). In contrast, a small dose of UVR in stage 2 disrupted the expected genome-wide transcriptome changes, demonstrating that the diatoms were less efficient in transitioning through and adopting appropriate physiologic states. This decreased capability to restore the physiological state to the corresponding environment appeared much earlier (in stage 2) under LC conditions, relative to HC cultures  a transition from nighttime to daytime)35. Upon losing this property, complex systems become sensitive to critical transitions27 and may exhibit slow or irreversible recovery from stress. Loss of relational resilience occurred in the stage just prior to collapse—in the second stage for LC cultures and in the third stage for HC cultures. This loss of relational resilience at the transcriptome level manifests in increased variation in photosynthetic efficiency of the cultures through transitions across the four physiological states within each stage. While there were minimal changes in the coefficient of variation (CV) of Fv/Fm (see Methods) across all replicates from cultures with no UVR stress , the CV of UVR-stressed cultures increased significantly in the stage preceding collapse , occurring in stage 2 under LC and stage 3 under HC conditions  of the stress test , light-harvesting, and central carbon metabolism. However, there was evidence that the improved resilience of diatoms under HC conditions could have resulted in part from the reduced requirement of CCMsThalassiosira spp. increased significantly from 14% to 37% of the phytoplankton composition of a natural community, when they were subjected to elevated CO2 and UVR in a mesocosm study58. Increased CO2 availability, however, is not the only change that diatoms will experience in future oceans. Decreased Fe bioavailability in an acidified ocean could have an opposite effect by increasing stress and inhibiting growth of T. pseudonana7. Given the variability in sensitivities of different phytoplankton and even species to different factors such as UVR, temperature, or nutrient limitations59, a multi-factorial experiment is necessary to understand the complex trade-offs in dealing with these combinatorial environmental changes. The framework and tools developed in this study can be adapted for conducting such stress tests with more factors and on a broader range of organisms in order to assay and predict how natural marine microbial populations will fare in response to ocean acidification.Consistent with our findings, abundance of a T. pseudonana (CCMP1335) grown in custom-made 1.5 L photo-bioreactors with enriched artificial seawater medium60 modified to have reduced levels of nitrate (~65 μM). Axenic T. pseudonana cultures were acclimated to 300 and 1000 ppm CO2 (mixed air) under a 12:12 h L:D regime for two consecutive growth cycles before being transferred to sterile nitrate-limited photo-bioreactors to a cell density of approximately 1 × 105 cells mL−1 (see Supplementary Methods). UVR exposures were performed using Daavlin 305-12BB UVB and 350 12 UVA lamps. Experiments were performed in triplicate for both conditions . On average both HC and LC replicates experienced individual contributions of 0.33 mW cm−2 UVA  and 0.16 mW cm−2 of UVB  for stage 2 totaling approximately 0.5 mW cm−2 of UVR. Culture density was monitored by direct cell counts using a standard hemocytometer. Photosynthetic efficiency  was obtained from the maximal fluorescence (Fm) and variable fluorescence (Fv) using the Phyto-PAM (Pulse Amplitude Modulated) Phytoplankton Analyzer. Variable fluorescence was calculated from Fm to Fo, where Fo is the fluorescence yield when cells are dark acclimated. The pH of growth medium was determined spectrophotometrically using the indicatory dye m-cresol purple61. Total dissolved inorganic carbon (DIC) was measured using an Apollo SciTech  Model AS-C3 and Li-COR LI-7000 CO2/H2O analyzer from filtered (0.2 μm) samples. Nitrate level was determined by Szechrome NAS colorimetric analysis as per the manufacturer’s protocol (Polysciences Inc.). Specific growth rate μ (day−1) was calculated from the linear regression of the natural log transformations of the cell concentrations vs. time (days) over the exponential phase of growth7. Growth curves were plotted by fitting growth data to a logistic model that includes the seeding estimates of maximum cell growth , growth rate, and length of the lag phase62 (please see the equation in the Supplementary Methods).All experiments were performed with the model diatom Samples were harvested from early and late exponential phase cultures, during the light and dark phase , and vacuum filtered onto 0.2 μm filters  and immediately flash frozen in liquid nitrogen  using Cufflinks68. Custom scripts were used to call different computational tools, each with specific parameter settings.Read files were cleaned with Trimmomatic version 0.33To test similarity between transcriptomes of biological replicates, we performed a Spearman’s rank correlation coefficient analysis. To reduce noise, transcripts with very low expression (below 5 FPKM) were excluded from the analysis. The remaining transcripts resulted in a compendium of more than 8000 expressed genes consistently included at each comparison, thus providing a global view of replicate similarity.10-transformed FPKM across the two discriminated conditions. Altogether, 58 descriptor transcripts of light and dark states, and 218 descriptor transcripts of early and late growth phase  were used to identify transcripts that could discriminate between (i) daytime and nighttime states, and (ii) early and late phase of growth. For a transcript to qualify as a light/dark or early/late state descriptor, its expression pattern had to (1) change in a statistically significant manner, and by twofold and (2) have at least one average standard deviation separation in logλi for each transcript i from its expression value κi. Initially, during selection of state descriptors, we obtained for each transcript two expression distributions from stage 1, ϕα and ϕβ whose medians define the expected expression values Q2(ϕα) and Q2(ϕβ) for each physiological state, that is, light/dark and early/late for light cycle and growth phase phenotypic variables, respectively. Next, we first identified whether κi was closer to Q2(ϕα) or Q2(ϕβ), using a piecewise function δ,ϕα and ϕβ using another piecewise function ϵ,ϕ, we linearly interpolated λi from Each dimension-specific coordinate was calculated separately, as a weighted average for each descriptor,κi located at the gap θ within ϕα and ϕβ, we linearly interpolated λi as,θc is the center of the gap θ.In the case that U test was used to assess the significance of distribution differences.To assess the variability among culture replicates during each stage, we computed the Euclidean distance among all sample replicates for each time-point in the state space for LC and HC conditions. A Mann–Whitney https://github.com/adelomana/viridis.The custom codes for growth curve, expression quantification, and transcriptome state analyses are available at PRJNA386016.All sequences supporting the findings of this study are publicly available from the National Center for Biotechnology (NCBI) Sequence Read Archive (SRA), accession code Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1