The QX-type infectious bronchitis virus (IBV) has become the predominant genotype worldwide in recent years and has caused serious economic losses to the chicken industry. The most significant feature of QX IBV is that its infection in the early growing stage can cause abnormal oviduct development, resulting in a high proportion of ‘false layers’ in poultry flocks of laying hens and breeders. However, few studies have evaluated whether infections of QX-type IBV in laying stages can also cause severe pathological changes in the oviduct.In this study, 300-day-old specific-pathogen-free chickens were infected either with the QX-type strain QXL or Massachusetts (Mass)-type strain M41 to compare their pathogenicity on different segments of the oviduct.Both the QXL and M41 strains successfully replicated in all segments of the oviduct; however, the QXL strain was more highly distributed in mucosal layer and caused severe lesions in the lamina propria, including interstitial dilation, inflammatory cell infiltration, and distinct expansion of tubular glands. Moreover, the QXL strain induced high expression of proinflammatory cytokines and cytotoxic molecules in the majority of segments in the oviduct. Further research found that the QXL strain may affected the formation of shell membranes and eggshells by inhibiting the expression of type I collagen and CaBP-D28k.Our results indicate that the QX-type IBV is more pathogenic than Mass-type IBV to oviduct in laying phase. Collectively, these findings provide detailed information on the pathological changes in different segments of the oviduct in laying phase, which could offer a better understanding about the pathogenicity of IBV.The online version contains supplementary material available at 10.1186/s12985-022-01788-0. Avian infectious bronchitis (IB) is a highly contagious, acute viral respiratory disease caused by IB virus (IBV), which primarily infects chickens . As a re2+ for shell formation [In China, QX-type IBV was first reported to be isolated from a broiler chicken flocks that had proventriculitis in 1997 in Qingdao, Shandong province , and in ormation . TherefoThe aim of this study was to provide a better understanding of the pathogenicity of IBV. To this end, the QX-type strain QXL and the Mass-type strain M41 (primarily causing respiratory symptoms) were used to investigate and compare pathogenicity in different segments of the oviduct. Pathological changes were evaluated by examining the antigen distribution, lesions, and expression of proinflammatory cytokines, cytotoxic molecules, type I interferon and eggshell formation-related genes.SPF embryonated chicken eggs were purchased from Beijing Boehringer Ingelheim Vital Biotechnology Co., Ltd. . SPF white leghorn chickens were purchased from Jinan Sipai Furui Livestock Technology Co., Ltd. .–1–10–8), five replicate samples of each dilution were inoculated into 10-day-old SPF embryonated chicken eggs, and the 50% chicken embryo infectious dose (EID50) was calculated using the method of Reed and Muench [The QX-type IBV strain CK/CH/JS/2010/12 (abbreviation: QXL) was isolated in 2010 from the trachea and kidney of chickens in a broiler flock exhibiting respiratory signs and death . Mass-tyd Muench .4 EID50 of IBV strains QXL and M41, one group per strain. Birds in the control group were administered 200 μL of saline solution via the oculonasal route. On days 4 and 8 post inoculation, three animals from each group were randomly selected and euthanized by cervical dislocation to evaluate macroscopic lesions in the oviduct. Tissue samples from the same regions of the infundibulum, magnum, isthmus and uterus of each bird were collected . Birds in two challenge groups were inoculated via the oculonasal route with 200 μL of allantoic fluid containing 10The four segments of the oviduct were fixed in 10% neutral-buffered formalin, processed via the standard histological procedure, embedded in paraffin wax, and cut into 4 μm sections. Some of the paraffin sections were stained with Hansen’s hematoxylin and eosin for histological observation, whereas other sections were prepared for immunohistochemistry (IHC) to detect the intensity of the viral antigen. Briefly, sections were incubated with 10% (v/v) goat serum (blocking solution) for 30 min. They were then incubated with a 1:15,000 dilution of mouse monoclonal antibody to IBV N protein at 37 ℃ for 2 h . After w18  according to the manufacturer’s instructions. The reaction was performed at 42 °C for 30 min and at 85 °C for 5 s for cDNA synthesis. The RT-qPCR mixture was composed of 10 μL AceQ® qPCR SYBR Green Master Mix , 0.4 μL of forward primer, 0.4 μL of reverse primer, 7.2 μL of nuclease-free water and 2 μL cDNA (or nuclease-free water for the control). The thermal profile for RT-qPCR was 95 °C for 5 min, followed by 40 cycles of 95 °C for 10 s, 60 °C for 30 s, melting at 95 °C for 15 s, 60 °C for 60 s and 95 °C for 15 s using a LineGene 9600 Plus . The primers used for RT-qPCR were described previously [−ΔΔCT method [Total RNA from different segments of the oviduct (100 mg tissue from each segment) was extracted using an Ultrapure RNA Kit . The concentration of RNA in each sample was measured using an Ultra micro sample spectrophotometer , and then 1 μg RNA was reverse transcribed using an EasyScript® Reverse Transcriptase  Kit  and Oligo (dT)eviously , 22. TheT method .P < 0.01, and extremely significant at P < 0.0001.GraphPad Prism 8.3 software  was used to analyze all statistical data via one-way analysis of variance. Differences between the challenge and control groups were considered statistically significant when the P-value was < 0.05, highly significant at To evaluate the distribution of viral antigen in different segments of oviduct, the paraffin sections were stained with IHC method. The results of IHC showed that the presence of QXL strain antigen was widely detected in the mucosal epithelial cilia and lamina propria Fig.  C2. The The H.E staining method was used to evaluate the pathological changes in different segments of oviduct. In the control group, the mucosal epithelium of the infundibulum, magnum, isthmus and uterus was lined by a ciliated pseudostratified epithelium, and the lamina propria was filled with tubular glands Fig.  A2, C2, To evaluate the degree of inflammation in each segment of the oviduct, the expression of proinflammatory cytokines  was detected 4 and 8 days after infection. Expression of IL-6 was significantly higher in the QXL group than in the control group in the isthmus at 4 days and in the uterus 4 and 8 days after infection, whereas its expression was significantly lower in both the QXL and M41 groups than in the control group in the infundibulum and magnum at 4 days Fig. A. The exCytotoxic molecules (granzyme and perforin) and IFN-α were subsequently detected at 4 and 8 days after infection. IFN-α expression was significantly higher in the QXL group than in the control group in the infundibulum at 8 days and in the magnum at 4 days , dendritic cells (DCs), and B cells to regulate adaptive immune responses [Generally, the host defends against intracellular viruses via classical inflammatory responses and antiviral immune responses, which are mediated by interferons (IFNs). IFN-γ is a key cytokine for Th1-controlled responses, which is essential for controlling intracellular pathogens . IFN-γ cesponses . The curesponses .Infection with IBV can affect the quality of eggs, such as soft shell eggs and sand shell eggs. Therefore, we evaluated the expression of genes involved in eggshell and eggshell membranes formation. Type I collagen is expressed in the isthmus, and the eggshell membrane forms during the passage of eggs through the oviduct . PreviouThe findings presented in this study may help improve the knowledge on QX-type IBV pathogenicity during the laying phase of chickens, and develop strategies to interfere with this infection. However, this study is primarily a description of the phenomenon, the pathogenesis of QX-type IBV to oviduct need the further study. Overall, our findings highlight the high pathogenicity of QX-type IBV to different segments of the oviduct in laying phase, which primarily manifests as marked pathological changes in the lamina propria and disordered expression of genes involved in eggshell and eggshell membranes formation.Additional file 1. Anatomic structure of the oviduct. The red dotted box represents the sampling site.


Down syndrome (DS) is the primary genetic cause of intellectual disability (ID), which is due to the triplication of human chromosome 21 (HSA21). In addition to ID, HSA21 trisomy results in a number of neurological and physiological pathologies in individuals with DS, including progressive cognitive dysfunction and learning and memory deficits which worsen with age. Further exacerbating neurological dysfunction associated with DS is the concomitant basal forebrain cholinergic neuron (BFCN) degeneration and onset of Alzheimer’s disease (AD) pathology in early mid-life. Recent single population RNA sequencing (RNA-seq) analysis in the Ts65Dn mouse model of DS, specifically the medial septal cholinergic neurons of the basal forebrain (BF), revealed the mitochondrial oxidative phosphorylation pathway was significantly impacted, with a large subset of genes within this pathway being downregulated. We further queried oxidative phosphorylation pathway dysregulation in Ts65Dn mice by examining genes and encoded proteins within brain regions comprising the basocortical system at the start of BFCN degeneration (6 months of age). In select Ts65Dn mice we demonstrate significant deficits in gene and/or encoded protein levels of Complex I-V of the mitochondrial oxidative phosphorylation pathway in the BF. In the frontal cortex (Fr Ctx) these complexes had concomitant alterations in select gene expression but not of the proteins queried from Complex I-V, suggesting that defects at this time point in the BF are more severe and occur prior to cortical dysfunction within the basocortical circuit. We propose dysregulation within mitochondrial oxidative phosphorylation complexes is an early marker of cognitive decline onset and specifically linked to BFCN degeneration that may propagate pathology throughout cortical memory and executive function circuits in DS and AD. Down syndrome (DS) is caused by the triplication of human chromosome 21 (HSA21) and is the primary genetic cause of intellectual disability (ID). HSA21 triplication is present in approximately 1 in 700 live births and these individuals exhibit multiple systemic functional deficits, including heart conditions, increased incidence of leukemias, epilepsy, premature aging, and neurological deficits  were purchased from Jackson Laboratories  and mated at the Nathan Kline Institute. Mice were given n = 10) and age-matched normal disomic  male mice, with littermates between 2N and Ts mice used when possible . The BF was dissected to enrich for cholinergic neurons in the medial septal/ventral diagonal band region (~Bregma 1.35–0.26) as well as the left Fr Ctx dissected using standard coordinates from the mouse brain atlas  according to manufacturers’ specifications. A DNase digestion was performed twice sequentially before the final washes and RNA purification  using random hexamers as described previously  and 45S pre-ribosomal RNA , utilizing dropped lines for peak analysis area calculation. Detected proteins were compared to control protein (β-TubIII) and reported as the normalized percentage of control. Each protein was performed in triplicate on separate plate runs. Statistical analysis was conducted on each protein normalized to β-TubIII and modeled as a function of the mouse study group , using mixed effects models with random mouse effect to account for the correlation between repeated assays on the same mouse  utilizing a 1:4 dilution of the deproteinized sample according to the manufacturer’s specifications for the fluorometric assay. The fluorometric samples were read in duplicate on a plate reader . ATP concentration was calculated according to the manufacturer’s specifications. Statistical analysis was performed using a non-parametric method (Wilcoxon Test) due to the small sample size and some losses of the sample  according to manufacturer’s specifications with the following alterations, starting sample volume was reduced to 50 μl from 100 μl with 7.5 μl of TCA, and neutralization was performed with 5 μl of neutralization solution. Immediately following deproteinization, an ATP assay  was performed in duplicate for each sample  and Mt-Nd4l (p < 0.00228), Complex II, Sdha (p < 0.00846), Complex III, Mt-Cytβ (not significant), Complex IV, Mt-Cox2 (not significant), and Complex V, Mt-Atp8  also showed a downregulated trend , trend level decreases in Complex III and IV genes (Mt-Cytβp = 0.067 and Mt-Cox2 p = 0.079), and significant downregulation of Complex V member Mt-Atp8 , III , IV , and V  were found  to assess protein expression of select subunits from Complexes I-V in the BF and Fr Ctx within Ts65Dn mice and 2N littermates. When examining the digital traces in BF homogenates , we saw re found , which hp < 0.0307; We indirectly examined the functionality of the oxidative phosphorylation complex by biochemical analysis of ATP levels, which are the output of the ATP synthase Complex V. Due to the small size of mouse BF and the quantity of tissue needed for the ATP assay, we were only able to perform this measurement in Fr Ctx tissue. We found a significant decrease in ATP levels in trisomic Fr Ctx  in Fr Ctx  pathway responsible for mitophagy and impaired activity of PGC-1α pathway responsible for biogenesis (Valenti et al., in vivo DS and AD models are warranted.Mitochondrial dysfunction beyond the oxidative phosphorylation pathway has been linked to DS pathology including deficits in mitochondrial biogenesis, turnover, and mitophagy (Helguera et al., Mt-Nd4l or Mt-Atp8, as they were not detected by RNA-seq (Alldred et al., RT-qPCR analysis and protein chemistry in trisomic BF and Fr Ctx reveals downregulation within oxidative phosphorylation genes and proteins that are specific to the brain regions analyzed. We recognize there are limitations and caveats to the studies we conducted using this approach. For example, each of these complexes in the oxidative phosphorylation pathway consists of numerous subunits, and the current interrogation was limited to one to two genes or proteins per complex. It is possible that other Complex I-V subunits will not be differentially regulated, although the larger number of changes identified by IPA and KEGG analysis from the MSN BFCN RNA-seq study of ~6 MO Ts65Dn mice and 2N littermates analysis indicates BFCNs are significantly vulnerable and display an abundance of deficits in oxidative phosphorylation and mitochondrial function transcripts (Alldred et al., In conclusion, select dysregulation of oxidative phosphorylation pathway members is found at the RNA and encoded protein levels within the vulnerable basocortical circuit in an established model of DS and AD at a timepoint where BFCN degeneration is occurring. Defects appear to initiate in the BF and travel in the synaptic pathway that connects this vulnerable region to a cortical terminal field associated with memory and executive function. These data suggest deficits in oxidative phosphorylation in the DS and possibly AD brain may be circuit driven, and more specific to vulnerable brain regions than previously appreciated, especially in the context of neuropathological disorders and age–related cognitive decline.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by IACUC Nathan Kline Institute.MJA GES, and SDG designed the experiments. MJA performed experiments. SHL, MJA, and SDG performed analysis of data. MJA and SDG wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


N = 81), aged 16–17, completed a response inhibition task while undergoing fMRI brain imaging and reported on their parents’ education, one component of socioeconomic status. A region of interest analysis showed that parental education was associated with brain activation differences in the classic response inhibition network  despite the absence of consistent parental education-performance effects. Further, although activity in our main regions of interest was not associated with performance differences, several regions that were associated with better inhibitory performance  also differed in their levels of activation according to parental education. Taken together, these results suggest that individuals from households with higher versus lower parental education engage key brain regions involved in response inhibition to differing degrees, though these differences may not translate into performance differences.Response inhibition and socioeconomic status (SES) are critical predictors of many important outcomes, including educational attainment and health. The current study extends our understanding of SES and cognition by examining brain activity associated with response inhibition, during the key developmental period of adolescence. Adolescent males ( Across both epidemiological and psychological studies, early socioeconomic disadvantage is associated with health risk behaviors3, premature mortality5, poor cardiovascular health6, lower levels of achievement later in life7, depression8 and other long-lasting health conditions such as substance use dependence11. Socioeconomic disadvantage also shapes critical neural pathways underlying core executive functions including the ability to override prepotent responses, known as response inhibition, a type of inhibitory control16. Although previous literature has identified a relationship between SES and response inhibition16, different indicators of SES may relate to response inhibition in the brain in different ways. Thus, additional research is needed to further elucidate how individual indicators of SES relate to response inhibition processes in the brain, which is the focus of the current manuscript.Socioeconomic status (SES) is a critical factor in determining an individual’s access to both economic and social resources1. In this study, we focus on parental education as it is often used as an index of early socioeconomic disadvantage and is fairly stable from childhood through adolescence17. High levels of parental education are associated with greater access to nonmaterial resources , as well as material resources . Higher levels of parental education are also positively related to children’s academic achievement20, and negatively associated with risky behaviors and impulsive decision making in adulthood21.Indicators of SES typically include parental education, occupation, and household income, which are typically intercorrelated with one another23. Response inhibition is a type of inhibitory control distinct from attentional inhibition , which refers to the ability to resist interference or distractions within a person’s environment23. If impaired, response inhibition can lead to poor physical and mental health outcomes, such as obesity and overeating26, as well as substance use29.Response inhibition is a key executive function that often facilitates positive health outcomes by reducing maladaptive risky behavior. Response inhibition is the ability to resist impulsive behavioral responses in service of responses that are consistent with a person’s goals33). Among these brain regions, one primary pathway, the frontal-subcortical pathway, has been consistently related to response inhibition in existing samples30. The frontal-subcortical pathway discussed by Aron & Poldrack (2006) includes right lateralized activity in the inferior frontal gyrus (IFG), which excites the subthalamic nucleus (STN), and in turn excites the globus pallidus (GP) during response inhibition.At the neural level, several brain regions have been associated with successful response inhibition, including the basal ganglia, superior, middle and inferior frontal gyri, precentral gyrus, inferior parietal lobule, insula, angular gyrus, supramarginal gyrus, superior and middle temporal gyri, pre-supplementary motor area, and anterior cingulate cortex  examined the relationship between parental income, education, and neighborhood poverty on bilateral IFG activation response inhibition performance and found that greater neighborhood poverty was associated with decreased activity in the IFG, and IFG activity during inhibitory control (no-go > go) was positively correlated with inhibitory performance. However, parental education was not associated with IFG activity during inhibitory control or with inhibitory performance. Other recent studies showed that poverty is associated with performance on cognitive control tasks43, and that lower SES is associated with reduced inhibitory control on behavioral tasks, despite not finding corresponding effects in the brain44. Although these results support the notion that early socioeconomic adversity of different types may shape the development of inhibitory control, more research is needed regarding how parental education affects behavioral and brain measures of response inhibition, a key executive function in avoiding risky behaviors and protecting health.However, only a limited amount of research examines SES and response inhibition and results so far have been mixed concerning SES effects on task performance, brain activity, and the relation between the two measures46. We examined the relationship between brain activity measured with fMRI during a go-no-go response inhibition task46 and participants’ reports of their parents’ education levels in a sample of male teenagers. If parental education is indicative of socioeconomic status and promotes development of regulatory control mechanisms such as response inhibition, then we would expect increased activation of the frontal-subcortical pathway underlying response inhibition in those with high, relative to low, levels of parental education. Our primary analyses examined whether parents’ education was associated with neural activity in the frontal-subcortical pathway during response inhibition. Second, we examined whether neural activity in the frontal-subcortical pathway during response inhibition varies by behavioral inhibitory performance. Third, we examined whether the relationship between neural activity in the frontal-subcortical pathway and task performance depended on parents’ education. Finally, we conducted exploratory whole brain analyses to examine additional relationships between neural correlates of response inhibition and parental education.In this study, we aim to address this need by examining the effects of parental education as an index of early socioeconomic advantage or disadvantage on neurobehavioral correlates of response inhibition in a go-no-go task47. Efficiency scores ranged from 0.34 to 0.73 . The correct percentage of inhibitory responses made on the go/no-go task ranged from 46.7 to 96.7% . The average response time on go trials ranged from 0.26 to 0.54 s . Overall, the range of scores on our behavioral measures suggests that there were not floor or ceiling effects associated with performance.Our primary measure of inhibitory performance was efficiency during the go-no-go task, calculated as the average go trial reaction time divided by the proportion of correctly inhibited no-go trialsM = 4.78, SD = 1.16), ranging from an average of a high school diploma (min = 2) to an average of a graduate degree (max = 6). Independently, fathers and mothers had an average education of a bachelor’s degree , both ranging from a high school diploma (min = 2) to a graduate degree (max = 6). Fathers’ and mothers’ education were significantly correlated (t(75) = 5.08, p < 0.001, r = 0.51, CI = ).Participants’ self-reports of their parents’ education was measured as the average score between the fathers’ and mothers’ education. Parents had an average education of a bachelor’s degree  = − 0.72, p = 0.472, r2 = 0.01, CI = ; Fig. We examined whether there was a relationship between performance measured during the go/no-go task and parents’ education, controlling for cohort sample. No significant relationship was found between parents’ education and our main measure of inhibitory performance, efficiency scores, , which make up the classic frontal-subcortical pathway48 during correct inhibitory trials compared to correct go trials. This analysis used the following model: ROI = β1(Parents’ Education) + β2(Study) + ε, where Study is a covariate controlling for the two cohorts pooled for these analyses.Our primary brain region of interest (ROI) consisted of the union of the right IFG, and sub-portions of the right BG (STN and GP), which make up the classic frontal-subcortical pathwayM = 0.088, SD = 0.37) versus go trials  for our sample as a whole  = 8.17, p = 0.006, η2 = 0.03, CI = ; see Supplemental Table β = 0.35, t(68) = 3.10, p = 0.003, r2 = 0.12, CI = ; Fig. β = 0.44, t(65) = 3.88, p < 0.001, r2 = 0.19, CI = ), rather than mothers’ education  = 1.49, p = 0.140, r2 = 0.03, CI = ).We replicated past findings that activity within the classic response inhibition network was greater during correct no-go  = 0.25, p = 0.802, r2 = 0.00, CI = ). Additional analyses on sub-components of the efficiency score can be found in supplemental materials. Whole brain analysis exploring additional regions associated with performance is described below  during correct no-go versus correct go trials was significantly associated with behavioral performance. No significant relationship was found between the primary behavioral measure of performance , and response inhibition activity in our focal regions of interest,  during successful inhibitory control compared to those from households with lower parental education. The relationship between parents’ education and neural activity within this pathway remained significant when controlling for individual differences in performance. Thus, although participants with higher parental education showed greater activity within the classic inhibition network during inhibitory trials, this difference was not related to performance differences. Furthermore, parents’ education did not moderate the relationship between performance and neural activity within the classic inhibition ROI.Finally, we explored whether parents’ education and inhibitory performance  was associated with different levels of recruitment of brain areas outside the classic inhibition network, and whether differential recruitment of these regions was related to performance and parents’ education, respectively. To explore these possibilities, we conducted whole brain analyses, and examined relationships between regions significantly associated with parental education and inhibitory performance.First, we examined the main effect of parents’ education on neural activity during correct no-go trials compared to correct go trials throughout the brain. Our goal was to determine whether adolescents from households with different parental education differed in neural activity beyond our hypothesized brain regions of interest. Higher parental education was associated with increased activity in the middle temporal gyrus, angular gyrus, basal ganglia, and occipital cortex Table . No regiβ = − 0.24, t(67) = − 2.07, r2 = 0.06, p = 0.043, CI = ; β = − 0.21, t(67) = − 1.73, r2 = 0.04, p = 0.089, CI = ; respectively). No other regions were associated with efficiency scores, p > 0.250. Results pertaining to the components of efficiency  are reported in supplemental materials, Table Next, we examined whether individual differences within the regions identified in Table Given that activity within the classic inhibitory control ROIs was not associated with performance, might other areas of the brain play a role in inhibition and be associated with performance? To address this possibility, we examined the main effect of inhibitory performance on neural activity by correlating brain activation that was greater during correct no-go trials versus correct go trials with inhibitory performance. Results indicated that better performance (indexed by a lower efficiency score) was associated with increased activity in the angular gyrus, MTG, superior frontal gyrus, left middle frontal gyrus, ventral medial prefrontal cortex (VMPFC), and amygdala, among other regions Table . No actiβ = 0.29, t(68) = − 2.52, r2 = 0.08, p = 0.014, CI = ), VMPFC  = 2.14, r2 = 0.06, p = 0.036, CI = ), amygdala/hippocampus  = 2.64, r2 = 0.09, p = 0.010, CI = ), and MTG  = 2.45, r2 = 0.08, p = 0.017, CI = ) were significantly associated with higher parental education. Full results are reported in Table β = − 0.19, p = 0.016, CI = ), VMPFC , amygdala/hippocampus , and MTG ; See supplemental materials for full results from the tests of indirect effects.Finally, we examined whether individual differences in activity within the regions identified in Table 49. However, limited knowledge exists regarding how different components of socioeconomic status relate to behavioral and brain measures of response inhibition40, a key executive function that often facilitates positive health outcomes by reducing maladaptive risky behaviors. In this study, we examined the effects of parental education as an index of early socioeconomic advantage or disadvantage, associated with access to nonmaterial resources  and material resources , on neurobehavioral correlates of response inhibition in a go-no-go task. Although we found that parental education was associated with neural activity in the frontal-subcortical response inhibition pathway (rIFG + rSTN + rGP), this did not translate into performance differences, which we discuss in more detail below.Previous research supports the idea that differences in a family’s socioeconomic resources may shape the development of children’s cognitive control and executive function more broadly33.First, we replicated prior findings showing that, on average, core regions of the classic frontal-subcortical response inhibition pathway (rIFG + rSTN + rGP) were more activated during successful no-go vs. go trials. These findings support the hypothesis that increased neural activity in the rIFG + rSTN + rGP is associated with successful inhibition and suggest that our sample in aggregate is consistent with past reports41. Research on children and adolescents aged 7–18 also found that greater neighborhood poverty  was associated with lower activation of the IFG compared to those from higher income neighborhoods, however, parental education was not associated with IFG activity40. The findings from the current study extend these lines of research to include parental education  as an additional factor that is associated with differences in the neural correlates of inhibitory control among adolescents.Second, we tested whether participants whose parents had more or less education recruited the frontal-subcortical response inhibition pathway to differing degrees during successful inhibition. Our focal analysis showed that adolescents with more educated parents displayed significantly more activity in these classic response inhibition regions during successful inhibition. These findings are broadly consistent with previous research on SES and inhibitory control. For example, 14-year-olds at an advanced pubescent stage, who were from households with lower economic resources, showed decreased recruitment of neural regions associated with inhibitory control during a multisource-interference task. This included activity in the IFG, among other regions33 for participants from households with higher parental education. Adolescents with more educated parents also showed increased activity in the right MTG and right angular gyrus, during successful inhibition.Complementing our region of interest approach, we also conducted a whole brain analysis to determine whether neural regions outside of our hypothesized rIFG + rSTN + rGP pathway were recruited differently depending on parents’ education. Those with more educated parents displayed significantly more activity in part of the basal ganglia , among other regions, during successful response inhibition, consistent with the idea that the basal ganglia are more strongly associated with response inhibition32. In addition, increased activity in the angular gyrus has been implicated in response inhibition tasks involving working memory31. As such, these data are consistent with our broader finding that adolescents from higher versus lower parental education backgrounds in this sample more strongly recruited brain regions implicated in response inhibition.Follow up analyses showed that in addition to differing in their level of activation according to parental education, increased activity in the angular gyrus was significantly associated with greater efficiency overall, and significantly faster reaction times . A similar marginal association was observed for MTG. MTG and the angular gyrus are multimodal association areas that play multiple roles in cognition. Relevant to the current findings, in past meta-analytic research examining neural correlates associated with different variants of stop signal tasks, the MTG has been implicated in successful response inhibition for go/no-go tasks that involve complex stop signal rules50, raising the possibility that increased activity within the subcortical response inhibition pathway does not in fact contribute to better performance. It is nevertheless true that another study of SES, inhibitory control and brain activity did find a positive relation between inhibitory control and IFG activity40.Further, we examined whether neural activity in the rIFG + rSTN + rGP was associated with individual differences in response inhibition performance. We expected that increased activity in the subcortical response inhibition pathway would be associated with better task efficiency. However, that was not found here. Other studies have reported a lack of such a relation as well31 and increased activity in the VMPFC and amygdala/hippocampus  has been associated with inhibitory processing of emotional stimuli compared to neutral stimuli51.To further examine the relationship between neural processes associated with response inhibition, performance , and parental education we conducted a whole brain analysis that examined the main effect of inhibitory performance on neural activity during correct no-go trials compared to correct go trials. In addition to the MTG and angular gyrus identified above, several other regions were significantly associated with better efficiency, including the superior frontal gyrus, middle and inferior temporal gyrus, middle frontal gyrus, ventral medial prefrontal cortex (VMPFC), and amygdala/hippocampus. Among these regions, follow up ROI analyses found that increased activity in the middle frontal gyrus, MTG, VMPFC, and amygdala/hippocampus were significantly associated with greater parental education. Further, despite the lack of a direct effect, exploratory analyses revealed that there was an indirect effect of parental education on inhibitory performance, through brain activity in the middle frontal gyrus, VMPFC, amygdala/hippocampus, and MTG. The middle frontal gyrus has been associated with correct inhibitory processing44.Our exploratory whole brain analyses showing there was an indirect effect of parental education on inhibitory performance, through brain activity in the middle frontal gyrus, VMPFC, amygdala/hippocampus, and MTG also suggest that different brain regions might be relevant to performance for different indicators of SES. For example, although Tomlinson et al. (2020) did not find that activity in IFG was associated with parental education, they did observe differences in the IFG during correct inhibitory control based on neighborhood poverty levels, and also found that these differences were associated with behavior. In parallel, Spielberg et al. (2015) found increased activity in the anterior cingulate during response inhibition over a two-year period was associated with poorer inhibitory control among females, but not males, from lower SES backgrounds based on the Hollingshead Four-Factor Index of SES, which includes household education and occupational prestige. In addition, behavioral studies of inhibitory performance and SES  have found significant relationships between lower SES and lower inhibitory control performance52. One possibility is that if lower SES is associated with faster maturity, more mature brains may show less activation for a similar level of performance. However, future research is needed to explicitly test this idea. Of course, as already noted, activity in the frontal-subcortical response inhibition pathway may not always be the limiting factor on performance.Given previous findings that vary with respect to tasks, SES measures and even gender, the present findings could not have been anticipated. Parental education predicted brain activity in the frontal-subcortical response inhibition pathway, but this activity was not accompanied by behavioral differences in our sample of male teens. Nor were they accompanied by compensatory activity detected in other brain areas for those with lower parental education. Lower SES samples have shown faster maturity in other contexts53. This line of reasoning is consistent with the idea that social and economic environments shape the way we think54, and behave55.On the other hand, it is also possible that differences in brain activity are more sensitive measures of inhibitory processes, and we did observe that activation in regions tracking inhibitory performance also varied by SES. It is possible that in a larger sample of participants, from an even wider range of SES backgrounds, would reveal differences in performance by parental education, or that differences in performance might emerge over time. It is also possible that specific components of the inhibitory process may differ by a person’s parental education levels. It may be the case that individuals from low and high parental education backgrounds simply take different approaches to successful inhibitory control; differing approaches could result in different degrees and patterns of activation despite the absence of overall differences in efficiency. For example, functional differences could be a result of different learned cognitive strategies rather than environmental factors altering neural functioningFurther, we suggest that going beyond differences in performance, to differences in what gives rise to performance, has implications for intervention. Based on our brain imaging results in this study, an intervention or educational program that works to increase inhibitory control with teens from one level of SES cannot be assumed to work at a different level, especially since we observed different patterns of activation for participants’ with high and low parental education despite similar performance.Second, given that so much imaging research is carried out at R1 universities, where the subject populations are disproportionately from educated, middle/upper-middle class families, the brain-behavior relations inferred may not in fact be representative of the whole national population. Our findings alert us to the possibility that the literature  may not be fully generalizable.Future research that includes wider samples beyond our relatively focal sample of recently-licensed (16–17 year old), male, drivers will help address whether, and for whom, the neural differences observed translate into performance differences. In addition, though the current study focused on parental education as an index of early socioeconomic advantage or disadvantage, additional measures of SES, including parental income and occupation or neighborhood socioeconomic conditions may help further clarify the relationship between inhibitory processing in the brain and inhibitory performance. For example, it may be the case that parental education is a less robust predictor of inhibitory performance in comparison to other indices of SES, such as neighborhood poverty levels as found in Tomlinson et al. (2020). Taken together with past findings, our data highlight the value of accounting for SES when planning interventions, and testing the assumption that effects are equally effective across groups. These findings collectively highlight the importance of measuring and including participants from a wider range of SES in neuroscience investigations.37. Future studies should build upon the present study’s findings to examine whether socioeconomic factors such as parents’ education may affect key brain systems implicated in health risk behaviors.Given their relationships to both parents’ education and performance in this dataset, the MTG and angular gyrus may be key regions to focus on in future studies that aim to understand relationships between parental education, brain activity and performance. In addition, adolescence is an important developmental stage where prefrontal brain areas are not fully developed56, mothers’ education is often found to be associated with SES-related health differences57. It is possible that fathers’ education mapped more closely to these adolescents’ SES environments, given that this sample contained only male participants. For example, it may be that sons’ connectedness to their fathers could be driving these effects. Research on gender socialization suggests that parents tend to have a greater influence on same-sex children58 and educational attainment of mothers is less influential on their son’s educational attainment compared to daughter’s59. However, the relationship between parental education and neural functioning should be more closely examined in future studies.Interestingly, the current data found that functional differences in response inhibition processing were associated with parental education, mainly driven by fathers’ rather than mothers’ education. Although parental education is one of the main indices of SES1.Results from the current study extend recent findings that have begun to examine the relationship between socioeconomic advantage and disadvantage and the brain. We found that although behavioral efficiency did not differ, adolescents from households with lower parental education displayed significantly less activity in classic response inhibition regions (rIFG + rSTN + rGP) during a go/no-go task compared to adolescents from households with higher parental education. Furthermore, when examining whether neural activity associated with parents’ education during correct no-go trials compared to go trials was associated with inhibitory performance, we found that increased neural activity in the MTG and angular gyrus were associated with marginally better efficiency, and significantly faster reaction times. Finally, we conducted an exploratory whole brain analysis that examined neural activity associated with inhibitory performance  during correct no-go trials compared to go trials. We found that parents’ education had indirect effects on inhibitory performance through increased activity in the VMPFC, middle frontal gyrus, middle temporal gyrus, and amygdala/hippocampus. Taken together, these results show that individuals from higher and lower SES backgrounds recruit inhibitory control regions in the brain to differing degrees. Given that most studies of response inhibition have not included measures of SES, and that many studies of inhibitory performance have been conducted at R1 universities with relatively higher SES samples, there is a need for future studies to further examine the role of SES on neural processes supporting successful response inhibition, including parsing different components of SES such as parental education, income and other factorsN = 81) between the ages of 16 to 17 years old across two cohorts were recruited through the University of Michigan Transportation Research Institute as part of a series of larger studies examining teen driving behavior64. All participants were right-handed, did not suffer from claustrophobia, were not currently taking any psychoactive medications, had normal  vision, did not have metal in their body that was contraindicated for fMRI, and did not typically experience motion sickness, which could affect driving simulation testing . Of the original 81 participants recruited across two cohorts, 10 participants did not have useable fMRI data . Removing these participants resulted in a final sample size of n = 71. Legal guardians provided written informed consent and teens provided written assent.Adolescent males  in an fMRI scanner. Finally, they completed additional post-scan online survey measures including questions regarding parents’ education. All study procedures were approved by the University of Michigan IRB and performed in accordance with relevant guidelines and regulations.Parents’ education served as our primary indicator of socioeconomic advantage or disadvantage. Participants were asked what level of education their father and mother each had completed on separate 7-point scales, where 1 = less than high school, 2 = high school, 3 = trade school, 4 = associates degree, 5 = bachelor’s degree, 6 = graduate degree, and 7 = unknown. A combined parents’ education variable was created using the average score between the father and mother. Unknown levels of education (response = 7) were not included in the combined parents’ education score. All participants reported parental education for at least one parent.46. Participants were fitted with a scanner-compatible 5-finger response glove to record behavioral responses. On each trial , participants were presented with one alphabetic character at the center of the display. On go trials (letters A through F), participants were instructed to respond by pressing a button on the response box with their right index finger. On no-go trials (letter X), participants were instructed not to make any response .Inhibitory performance on the go/no-go task was measured by combining reaction time during go trials with the proportion of correctly inhibited no-go trials compared to the total number of no-go trials to create “efficiency scores” , which takes into consideration the tradeoff between speed and accuracyImaging data were acquired using a 3 Tesla GE Signa MRI scanner. Two functional runs were acquired for each participant (174 volumes per run). Functional images were recorded using a reverse spiral sequence . We also acquired in-plane T1-weighted images  and high-resolution T1-weighted images  for use in coregistration and normalization.http://dbm.neuro.uni-jena.de/vbm), and then normalized to the skull-stripped MNI template provided by FSL (“MNI152_T1_1mm_brain.nii”). Finally, functional images were smoothed using a Gaussian kernel (8 mm FWHM).To allow for the stabilization of the BOLD signal, the first four volumes (eight seconds) of each run were discarded prior to analysis. Functional images were despiked using the 3dDespike program as implemented in the AFNI toolbox. Next, data were corrected for differences in the time of slice acquisition using sinc interpolation; the first slice served as the reference slice. Data were then spatially realigned to the first functional image. We then co-registered the functional and structural images using a two-stage procedure. First, in-plane T1 images were registered to the mean functional image. Next, high-resolution T1 images were registered to the in-plane image. After coregistration, high-resolution structural images were skull-stripped using the VBM8 toolbox for SPM8  across individuals.48. More detailed ROI definitions can be found in supplemental materials. Percent signal change (for correct no-go > correct go) was extracted from this primary ROI for each participant using MarsBaR65; additional analyses broken out by sub-region can be found in supplemental materials. Our primary analysis examined whether parents’ education was associated with brain activity in this a priori defined ROI during correct inhibitory trials compared to correct go trials, using the equation ROI = β1(Parents’ Education) + β2(Study) + ε, where Study is a covariate controlling for the two cohorts pooled for these analyses.Our primary region of interest (ROI) consisted of the union of the right IFG, and sub-portions of the right BG (STN and GP), which make up the classic frontal-subcortical pathway Fig. 48. More 1(IP) + β3(Study) + ε, where IP is inhibitory performance), and whether the relationship between brain activity and task performance depended on parents’ education (ROI = β1(IP) + β2(Parents’ Education) + β3(Parents’ Education * IP) + β4(Study) + ε). All analyses were conducted in R (version 4.2.0). Linear models were fit using lm, repeated measures ANOVA was calculated using aov, and confidence intervals were calculated using confint in the Stats (version 4.2.0) package67. Beta coefficients were calculated using lm.beta in the QuantPsych (version 1.5) package68. Scatterplots were created using ggplot2 in the ggplot2 (version 3.3.5) package69. Mediation analyses were analyzed using mediate in the mediation (version 4.5.0) package70.Secondary analyses examined whether activity within our main regions of interest was related to inhibitory task performance (ROI = β1(Parents’ Education) + β2(Study) + ε and independently from inhibitory performance: WBA = β1(Efficiency Scores) + β2(Study) + ε. The whole brain analyses are reported with a threshold of p = 0.001, K > 57, based on a Monte Carlo simulation using 3dClustSim , corresponding to p < 0.05, corrected.In addition to our primary ROI analyses, exploratory whole brain analyses examined whether additional neural regions outside of classically reported inhibitory control regions of interest were associated with parents’ education and inhibitory performance  for correct no-go trials > correct go trials . Accordingly, we fit a regression model predicting activation in each voxel in whole brain analyses (WBA) from parental education: WBA = β1(Parents’ Education) + β2(Study) + ε; WBA = β1(Efficiency Scores) + β2(Study) + ε) were associated with efficiency scores and parents’ education, respectively, we conducted a follow up ROI analyses. Functional regions were identified based on peak clusters in Tables http://www.alivelearn.net/xjview). The following regression models were used to examine whether functional regions associated with parents’ education during correct no-go trials compared to go-trials were related to efficiency scores (fROI(Parents’ Education) = β1(IP) + β3(Study) + ε) and whether functional regions associated with efficiency scores during correct no-go trials compared to go-trials were related to parents’ education (fROI(Efficiency Scores) = β1(Parents’ Education) + β3(Study) + ε), controlling for study. Finally, exploratory mediation analyses were conducted for significant findings from our fROI analyses (fROI(Efficiency Scores) = β1(Parents’ Education) + β3(Study) + ε) in order to determine whether there was an indirect relationship between parents’ education and inhibitory performance through neural activity in these functional regions. A causal mediation analysis  was conducted to examine the indirect effect (c = c’ + ab). Results for the direct effect (c’), total effect (c), and proportion mediated.In order to determine whether functional regions identified in our whole brin analyses (WBA = βSupplementary Information.


Functionally, however, sea ice encoded fewer accessory traits and lower average genomic copy numbers for shared traits, though DNA replication and repair were elevated; in contrast, microbes in cryopeg brines had greater genetic versatility with elevated abundances of accessory traits involved in sensing, responding to environmental cues, transport, mobile elements (transposases and plasmids), toxin-antitoxin systems, and type VI secretion systems. Together these genomic features suggest adaptations and capabilities of sea-ice communities manifesting at the community level through seasonal ecological succession, whereas the denser cryopeg communities appear adapted to intense bacterial competition, leaving fewer genera to dominate with brine-specific adaptations and social interactions that sacrifice some members for the benefit of others. Such cryopeg genomic traits provide insight into how long-term environmental stability may enable life to survive extreme conditions.Subzero hypersaline brines are liquid microbial habitats within otherwise frozen environments, where concentrated dissolved salts prevent freezing. Such extreme conditions presumably require unique microbial adaptations, and possibly altered ecologies, but specific strategies remain largely unknown. Here we examined prokaryotic taxonomic and functional diversity in two seawater-derived subzero hypersaline brines: first-year sea ice, subject to seasonally fluctuating conditions; and ancient cryopeg, under relatively stable conditions geophysically isolated in permafrost. Overall, both taxonomic composition and functional potential were starkly different. Taxonomically, sea-ice brine communities (∼10 For DNA analyses and all ancillary measurements, we then collected 20 L of SB by hand-pumping into an acid-washed cubitainer, first rinsed with sample brine.We collected samples near Utqiaġvik, Alaska, during two field seasons in May 2017 and May 2018. Landfast, first-year sea ice was sampled near the Barrow Sea Ice Mass Balance site, operated by the University of Alaska Fairbanks , at 71.2In each year, we collected full-length sea-ice cores using a MARK II ice auger (Kovacs Enterprise) with a diameter of 9 cm. For two cores, vertical temperature measurements were made in the field at 5-cm intervals according to TM filter (MilliporeSigma) and immediately stabilizing it with RNAlaterTM  while still in the tunnel. The metatranscriptome sequencing library for CBIW later failed sequencing efforts and no longer appears in this study.Cryopeg brine (CB) was obtained through the Barrow Permafrost Tunnel, located at 71.2944 °N, 156.7153 °W and situated 6 m below the surface. The temperature inside the tunnel held at –6°C during our sampling work . Brines in situ brine temperatures at the Barrow Arctic Research Center. Cryopeg brines were held at –6°C and sea-ice brines at –1°C until further processing within 2–8 h. Sea-ice sections were melted into a filter-sterilized (0.22-μm pore size) artificial sea salt solution  at a 1:1 vol:vol ratio. For subsequent DNA extraction, maximum available volumes were filtered onto 47-mm GTTP Isopore filters , following the manufacturer’s instructions. To ensure free movement of the samples during bead beating, we cut filters into stripes using sterilized scalpels and forceps, and performed two extractions per sample, each containing half a filter. Isolated DNA was eluted in 60 μl nuclease-free water , and both extracts from the same filter were pooled and stored at –20°C.TM . For RNA extractions, we used the DNeasy PowerWater Sterivex Kit , following the manufacturer’s instructions, with the following modifications developed by the QIAGEN microbiome team that allowed recovering RNA from the filter membranes without the need to cut open the plastic casing holding the membrane: After removing RNAlaterTM from the casing using a sterile 3-ml syringe, we followed protocol, but added 20 μl of β-mercaptoethanol (βME) for every 880 μl of Solution ST1B in step 2. Further, we modified step 7 and incubated the filter unit at 70°C for 10 min, and in step 19 added 1.5 ml of Solution MR, as well as 1.5 ml of 100% ethanol. We eluted the isolated RNA in 50 μl of sterile RNase-free water  and performed a subsequent DNA digest by adding 7 μl DNase buffer (10×) , 10 μl DNase I recombinant , and 2 μl RNAsin RNase inhibitor . The mix was then incubated for 20 min at 37°C, and subsequently for 10 min at 56°C before placing it on ice. Finally, RNA was cleaned and concentrated using the RNeasy MinElute Cleanup Kit  and the final product was eluted in 40 μl RNase-free water and stored at −80°C.Prior to any RNA work, we cleaned all working areas and equipment with 70% Ethanol, followed by a wipe with RNaseZapFor sequencing, we shipped nucleic acid extracts on dry ice to the DOE Joint Genome Institute (JGI). Here, DNA was sheared to 300 bp using the Covaris LE220 (Covaris) and size selected using SPRI beads (Beckman Coulter). The fragments were treated with end-repair, A-tailing, and ligation of Illumina compatible adapters  using the KAPA-Illumina library creation kit (KAPA biosystems) and 5–20 cycles of PCR were used to enrich for the final library. Sequencing of metagenomic libraries was performed on an Illumina NovaSeq sequencer to produce 2 × 151 base pair (bp) paired-end reads. Contaminant removal , trimming of adapters, and right-quality trimming of reads where quality dropped to 0 was done with BBDuk. BBDuk was also used to remove reads that contained four or more “N” bases, had an average quality score across the read of less than 3, or had a minimum length ≤51 bp or 33% of the full read length. Quality control removed between 0.2 and 9% of raw sequences, resulting in a total of 247–661 million quality-controlled reads per sample.Trimmed, screened, and paired-end Illumina reads were read-corrected using bfc (version r181) with -k 21. Reads with no mate pair were removed. The remaining reads were assembled using SPAdes using the settings “–only-assembler -k 33,55,77,99,127 –meta.” The entire filtered read set was mapped to the final assembly and coverage information generated using BBMap with default parameters except ambiguous = random. See TM rRNA Removal Kit (Epicenter). Stranded cDNA libraries were generated using the Illumina Truseq Stranded RNA LT kit. The rRNA depleted RNA was fragmented and reversed transcribed using random hexamers and SSII (Invitrogen) followed by second strand synthesis. The fragmented cDNA was treated with end-pair, A-tailing, adapter ligation, and 10 cycles of PCR. Low input libraries were sequenced on an Illumina NovaSeq sequencer, generating 2 × 151 bp long paired-end reads. Contaminant removal and quality control was conducted in the same way as for the metagenomic reads (see above). The final filtered fastq contained 48,612,144 and 23,642,934 reads in the cryopeg and the sea-ice metatranscriptome, respectively . For coverage information, BBMap was used to map the quality-filtered reads against the metatranscriptome assemblies, as well as against the corresponding metagenomic reference assemblies with default parameters except for ambiguous = random.Functional and structural annotation of the generated metagenomic and metatranscriptomic assemblies was performed through the DOE-JGI Metagenome Annotation Pipeline (MAP) . InformaWe used the phyloFlash pipeline  to screeCandidatus Nitrosopumilus, the most abundant archaeal community member, was included as tree outgroup despite relative abundance values <1%. The tree and the corresponding community abundance data were visualized with iTOL v4 (We used SPAdes (as implemented in phyloFlash) for a targeted assembly of full-length SSU rRNA sequences from the identified SSU rRNA reads. From the resulting 460 reconstructed sequences, we selected those of dominant prokaryotic community members (genera of >1% relative abundance) for multiple sequence alignment using MAFFT Q-INS-I . We used iTOL v4 .For comparative analyses of the functional potential encoded in the microbial communities in cryopeg brines and sea ice, we focused on molecular functions represented in the KEGG Orthology (KO) database . Here, gTo allow a direct and biologically meaningful comparison between samples, we normalized all metagenomic datasets using Metagenomic Universal Single-Copy Correction (MUSiCC) with the settings “–normalize –correct learn_model” . Rather As individual KOs can be associated with multiple higher-level functions, we used Evidence-based Metagenomic Pathway Assignment using geNe Abundance Data (EMPANADA) to infer the prevalence of different KO pathways and modules in each sample . Here, tvegan package v.2.5.6  followed by a post-hoc Tukey pairwise significance test to assess the significance (p ≤ 0.05) of variance in observed richness and Shannon diversity between both brine environments. We performed a Principal Component Analysis (PCA) for the analysis of beta diversity patterns in our data. We used the ampvis2 package v.2.5.8  correction with a corrected P < 0.05 (pheatmap R package v1.0.12 (ggplot2 package v3.3.2 (We used the e v1.1.0  to perfoP < 0.05 . We visu v1.0.12  and usede v3.3.2 .n = 6) and sea-ice brines and section melts (n = 5). Assemblies of individual datasets resulted in overall larger and more fragmented assemblies from sea ice than from cryopeg, with sea-ice metagenomes having, on average, more but shorter contigs, and being enriched for singleton contigs and unassembled reads (p < 0.01) and more diverse (p < 0.01) community in sea ice than in cryopeg brines (p < 0.01) though not functional diversity  and functionally (p < 0.01). In sea ice, the strongest drivers of the taxonomic variance from cryopeg brines were members of Bacteroidetes, mainly Polaribacter and unclassified Flavobacteriaceae, as well as the gammaproteobacterial genera Paraglaciecola, Glaciecola and Colwellia, and the alphaproteobacterial genus Octadecabacter and SAR11 clade  were the most transcriptionally active members in CB4  and not to its corresponding metagenome , chaperone-mediated and stress-associated protein folding (K04077: chaperonin GroEL) , and purin silico features commonly enriched in both sea ice and cryopeg brines. Results confirmed that communities in both brines encode molecular functions relevant for all of the key cold-adaptation features introduced above. We also observed clear differences, however, in average gene abundance and implementation strategies. Compared to sea-ice communities, microbes in cryopeg brines invested significantly more of their genomic content in the transport of phospholipids and biosynthesis of fatty acids, peptidoglycan, lipopolysaccharides and lysine  readily released by sea-ice algae during seasonal salinity stress  would seMicrobes have evolved multiple strategies to overcome unfavorable environmental conditions, including ways to persist through periods of suboptimal nutrition, from compound storage and salvage to the use of metabolic shunts. During evaluation of our samples by epifluorescence microscopy , nitrogen reserve polymers and cyanophycin. The relevant genes for PHA synthesis and breakdown, PHA synthase, 3−hydroxybutyrate dehydrogenase and PHA depolymerase, were present in both brine types, with no significant differences, but we observed higher gene abundances for the synthesis and degradation of cyanophycins in sea-ice communities. Cyanophycins are amino acid polymers (polyamines) that cyanobacteria and some heterotrophic bacteria, including cabacter , can acccabacter . Biosyntlyamines  and its lyamines . Respirae brines .Likewise, the use of the γ-aminobutyrate (GABA) shunt may constitute an economical solution to thriving under stressful and potentially unfavorable periods of nutrient limitation in cryopeg brines, where we observed significantly higher gene abundances for this pathway than in sea ice . This shIn sea-ice communities, we found a significantly greater potential for microbes to be economical by recycling sulfur-containing compounds through the methionine salvage pathway . AlthougWhile maintenance of essential cellular processes and retention of membrane fluidity for solute exchange ensure survival in subzero brines, competitive advantage may be acquired through accessory traits, e.g., the ability to sense environmental stimuli and changes, and be metabolically versatile to adjust to microniche requirements. We observed strong disparities in the accessory genomic potential encoded by communities in the two brine types, with some of the most marked differences in their environmental information-processing capacities . The genMyxococcus xanthus  genes in cryopeg communities, used by bacteria to alter the net charge of their cellular envelope and resist a variety of cationic antimicrobials  may favor the retention of genomic changes  in these extreme environments, as obtaining in situ oxygen measurements was not possible given the top priority to avoid introducing any contamination, particularly to the geologically isolated cryopeg brines.In the densely populated cryopeg brines, the high abundance of transposases together with high genomic copy numbers of numerous accessory traits and indications for the presence of plasmids suggest that these communities may undergo considerable genomic rearrangements, gene duplication events and horizontal gene transfer  changes . We lackIn stark contrast are the challenges faced by microorganisms within the brines of sea ice. Frequent disturbance of the physico-chemical conditions imposed by hourly to seasonal fluctuations in atmospheric temperature, paired with steep vertical gradients in temperature, salinity and nutrient availability, suggests that microbial inhabitants must also be versatile to survive and thrive. However, our results imply that many members of the sea-ice community invest less in the encoding of accessory traits than those in the cryopeg communities, given the lower average copy numbers of individual features. We suggest that a distribution of capabilities across multiple community members, though potentially leading to reduced fitness of some individuals, maintains the versatility of the community as a whole, with the possible benefits of genome streamlining and more rapid replication. The community dynamics in sea ice would then follow a temporal succession, as others have documented , rather in situ. As environmental conditions change with amplified warming in the Arctic, particularly for historically stable cryopegs in permafrost, knowledge of current microbial dynamics in these unusual communities will be valuable to anticipating their future impacts on the larger Arctic ecosystem. One may speculate that some genes specific to surviving the current extremes and others enabling intensive social interactions, as documented here, may no longer be expressed or maintained. Communities inhabiting fresher brines in thinner sea ice will more closely resemble their source seawater communities, and the inhabitants of cryopeg brines will face new competition as permafrost thaws and the brines begin to merge with the surface environment. We can hypothesize that the strong divergence in functional potential observed between both systems described here may fade as the geophysically isolated and stable cryopeg environment transitions into a more moderate and seasonally fluctuating state. Our metagenomic analyses thus emphasize the ecological importance of habitat stability in the face of climate change.Beyond the expected molecular adaptations that allow maintenance of vital cell functions, the survival and prosperity of bacteria in subzero brines appear to be shaped strongly by their abilities to use resources economically, to sense and respond to changes in their microenvironments, and to interact with other community members. The capability to autoregulate and induce growth arrest was a common feature and key mechanism for persistence during unfavorable conditions, including intense competition. An evaluation of the genomic potential of individual community members and efficient techniques to identify actively metabolizing members are needed to better resolve such dynamics in the future. Promising approaches include bioorthogonal non-canonical amino acid tagging (BONCAT), as preliminary results gave positive results in both brine types , and subsequent fluorescence-activated cell sorting (FACS)  and sequhttps://genome.jgi.doe.gov/portal/). For individual accession numbers per sample see https://www.ocean.washington.edu/story/Deming_Data_Archives.All generated metagenomes and metatranscriptomes analyzed in this study were made publicly available as raw reads, quality-controlled reads, and assemblies through the IMG system (JD conceived the study, with input from MS and JR. JR and JD conducted the field work and sampling. JR processed the samples, performed the DNA and RNA extractions, performed all the data analyses, and wrote the first draft of the manuscript. JD and MS supported the interpretation of results and critically revised the manuscript. All authors read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Fire, sometimes called biomass burning, is a key factor affecting many aspects of the Earth system, including climate change, ecosystems, land surface processes, the carbon cycle, atmospheric chemistry and human society . UnderstCharcoal fossils in sediments can provide fire information since the Silurian (about 420 million years ago) , potentiThe normal focus of fire studies in glacier ice is the chemical components, including characteristic ions (e.g. ammonium), black carbon, trapped air (e.g. methane and carbon monoxide), low-molecular-weight organic acids , persistent organic pollutants, resinic acids and monosaccharide anhydrides (e.g. levoglucosan) . Each ofThese chemical species often have multiple potential sources in addition to fire emissions ,4 and coad 1994 summer forest fire events over the Canadian Arctic regions were detected by ammonium, formate, levoglucosan and oxalate records in Greenland snow layers [ad 1908, 1895, 1863, etc.) were identified by abnormal peaks of ammonium, formate, glycolate, oxalate and acetate in Greenland ice cores [Due to the long-distance transport, fire signals detected in glacier ice are usually at extremely low levels when compared to those of the source regions . Althougw layers . Similarce cores . NeverthPolar ice sheets can provide more detailed information on fire after the Last Glacial Period ,6, and iad 1250 was reconstructed using nitrate, potassium and charcoal records in the Belukha ice core from the Siberian Altai; these records suggested that precipitation changes were the driving factor controlling fire changes. Some sporadic fire events have been reported in glacier ice on the Tibetan Plateau [Alpine glacier ice can provide some essential information about fire changes on regional scales ,7. The f Plateau . In compTo better understand ancient fire changes reconstructed in glacier ice, several associated issues need further attention in future work.The most notable issue regards the geochemical significance of fire tracers. A large concentration of photochemically active groups is present in the snowpack ,4, which−1) or ultra-trace (pg g−1) concentrations or even lower [Challenges in tracing fire sources are also an urgent issue. Those based on back trajectories can only provide rough results ,7–10 anden lower , which ien lower ,4.Precise dating of ice cores is critical for capturing the detailed characteristics of fire variations. Obtaining continuous results can reveal the frequency of fire events as well as longer-term temporal changes , especia