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Background: Major depressive disorder (MDD) and borderline personality disorder (BPD) often co-occur, with 20 % of adults with MDD meeting criteria for BPD. While MDD is typically diagnosed by symptoms persisting for several weeks, research suggests a dynamic pattern of symptom changes occurring over shorter durations. Given the diagnostic focus on affective states in MDD and BPD, with BPD characterized by instability, we expected heightened instability of MDD symptoms among depressed adults with BPD traits. The current study examined whether BPD symptoms predicted instability in depression symptoms, measured by ecological momentary assessments (EMAs)., Methods: The sample included 207 adults with MDD (76 % White, 82 % women) recruited from across the United States. At the start of the study, participants completed a battery of mental health screens including BPD severity and neuroticism. Participants completed EMAs tracking their depression symptoms three times a day over a 90-day period., Results: Using self-report scores assessing borderline personality disorder (BPD) traits along with neuroticism scores and sociodemographic data, Bayesian and frequentist linear regression models consistently indicated that BPD severity was not associated with depression symptom change through time., Limitations: Diagnostic sensitivity and specificity may be restricted by use of a self-report screening tool for capturing BPD severity. Additionally, this clinical sample of depressed adults lacks a comparison group to determine whether subclinical depressive symptoms present differently among individuals with BPD only., Conclusions: The unexpected findings shed light on the interplay between these disorders, emphasizing the need for further research to understand their association., Competing Interests: Declaration of competing interest NCJ has received a research grant from Boehringer Ingelheim as PI (though there is no salary support or direct payments to NCJ the grant funds his personnel and his ability to collect data). Additionally, NCJ receives speaking fees and royalties related to publishing a book through the Academic Press., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Anhedonia and depressed mood are two cardinal symptoms of major depressive disorder (MDD). Prior work has demonstrated that cannabis consumers often endorse anhedonia and depressed mood, which may contribute to greater cannabis use (CU) over time. However, it is unclear (1) how the unique influence of anhedonia and depressed mood affect CU and (2) how these symptoms predict CU over more proximal periods of time, including the next day or week (rather than proceeding weeks or months). The current study used data collected from ecological momentary assessment (EMA) in a sample with MDD (N = 55) and employed mixed effects models to detect and predict weekly and daily CU from anhedonia and depressed mood over 90 days. Results indicated that anhedonia and depressed mood were significantly associated with CU, yet varied at daily and weekly scales. Moreover, these associations varied in both strength and directionality. In weekly models, less anhedonia and greater depressed mood were associated with greater CU, and directionality of associations were reversed in the models looking at any CU (compared to none). Findings provide evidence that anhedonia and depressed mood demonstrate complex associations with CU and emphasize leveraging EMA-based studies to understand these associations with more fine-grained detail., Competing Interests: Declaration of competing interest NCJ has received a research grant from Boehringer Ingelheim as PI (though there is no salary support or direct payments to NCJ, the grant funds his personnel and his ability to collect data). Additionally, NCJ receives speaking fees and royalties related to publishing a book through the Academic Press., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The ATP-driven bicarbonate transporter 1 (BCT1) from Synechococcus is a four-component complex in the cyanobacterial CO2-concentrating mechanism. BCT1 could enhance photosynthetic CO2 assimilation in plant chloroplasts. However, directing its subunits (CmpA, CmpB, CmpC, and CmpD) to three chloroplast sub-compartments is highly complex. Investigating BCT1 integration into Nicotiana benthamiana chloroplasts revealed promising targeting strategies using transit peptides from the intermembrane space protein Tic22 for correct CmpA targeting, while the transit peptide of the chloroplastic ABCD2 transporter effectively targeted CmpB to the inner envelope membrane. CmpC and CmpD were targeted to the stroma by RecA and recruited to the inner envelope membrane by CmpB. Despite successful targeting, expression of this complex in CO2-dependent Escherichia coli failed to demonstrate bicarbonate uptake. We then used rational design and directed evolution to generate new BCT1 forms that were constitutively active. Several mutants were recovered, including a CmpCD fusion. Selected mutants were further characterized and stably expressed in Arabidopsis thaliana, but the transformed plants did not have higher carbon assimilation rates or decreased CO2 compensation points in mature leaves. While further analysis is required, this directed evolution and heterologous testing approach presents potential for iterative modification and assessment of CO2-concentrating mechanism components to improve plant photosynthesis., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Cyanobacterial CO 2 concentrating mechanisms (CCMs) sequester a globally consequential proportion of carbon into the biosphere. Proteinaceous microcompartments, called carboxysomes, play a critical role in CCM function, housing two enzymes to enhance CO 2 fixation: carbonic anhydrase (CA) and Rubisco. Despite its importance, our current understanding of the carboxysomal CAs found in α-cyanobacteria, CsoSCA, remains limited, particularly regarding the regulation of its activity. Here, we present a structural and biochemical study of CsoSCA from the cyanobacterium Cyanobium sp. PCC7001. Our results show that the Cyanobium CsoSCA is allosterically activated by the Rubisco substrate ribulose-1,5-bisphosphate and forms a hexameric trimer of dimers. Comprehensive phylogenetic and mutational analyses are consistent with this regulation appearing exclusively in cyanobacterial α-carboxysome CAs. These findings clarify the biologically relevant oligomeric state of α-carboxysomal CAs and advance our understanding of the regulation of photosynthesis in this globally dominant lineage.

The introduction of the carboxysome-based CO 2 concentrating mechanism (CCM) into crop plants has been modelled to significantly increase crop yields. This projection serves as motivation for pursuing this strategy to contribute to global food security. The successful implementation of this engineering challenge is reliant upon the transfer of a microcompartment that encapsulates cyanobacterial Rubisco, known as the carboxysome, alongside active bicarbonate transporters. To date, significant progress has been achieved with respect to understanding various aspects of the cyanobacterial CCM, and more recently, different components of the carboxysome have been successfully introduced into plant chloroplasts. In this Perspective piece, we summarise recent findings and offer new research avenues that will accelerate research in this field to ultimately and successfully introduce the carboxysome into crop plants for increased crop yields., (© 2024 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Major depressive disorder (MDD) is conceptualized by individual symptoms occurring most of the day for at least two weeks. Despite this operationalization, MDD is highly variable with persons showing greater variation within and across days. Moreover, MDD is highly heterogeneous, varying considerably across people in both function and form. Recent efforts have examined MDD heterogeneity byinvestigating how symptoms influence one another over time across individuals in a system; however, these efforts have assumed that symptom dynamics are static and do not dynamically change over time. Nevertheless, it is possible that individual MDD system dynamics change continuously across time. Participants (N = 105) completed ratings of MDD symptoms three times a day for 90 days, and we conducted time varying vector autoregressive models to investigate the idiographic symptom networks. We then illustrated this finding with a case series of five persons with MDD. Supporting prior research, results indicate there is high heterogeneity across persons as individual network composition is unique from person to person. In addition, for most persons, individual symptom networks change dramatically across the 90 days, as evidenced by 86% of individuals experiencing at least one change in their most influential symptom and the median number of shifts being 3 over the 90 days. Additionally, most individuals had at least one symptom that acted as both the most and least influential symptom at any given point over the 90-day period. Our findings offer further insight into short-term symptom dynamics, suggesting that MDD is heterogeneous both across and within persons over time. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Major Depressive Disorder (MDD) is a heterogeneous disorder, resulting in challenges with early detection. However, changes in sleep and movement patterns may help improve detection. Thus, this study aimed to explore the utility of wrist-worn actigraphy data in combination with machine learning (ML) and deep learning techniques to detect MDD using a commonly used screening method: Patient Health Questionnaire-9 (PHQ-9). Participants (N = 8,378; MDD Screening = 766 participants) completed the and wore Actigraph GT3X+ for one week as part of the National Health and Nutrition Examination Survey (NHANES). Leveraging minute-level, actigraphy data, we evaluated the efficacy of two commonly used ML approaches and identified actigraphy-derived biomarkers indicative of MDD. We employed two ML modeling strategies: (1) a traditional ML approach with theory-driven feature derivation, and (2) a deep learning Convolutional Neural Network (CNN) approach, coupled with gramian angular field transformation. Findings revealed movement-related features to be the most influential in the traditional ML approach and nighttime movement to be the most influential in the CNN approach for detecting MDD. Using a large, nationally-representative sample, this study highlights the potential of using passively-collected, actigraphy data for understanding MDD to better improve diagnosing and treating MDD., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Positive psychology interventions (PPIs) are effective at increasing happiness and decreasing depressive symptoms. PPIs are often administered as self-guided web-based interventions, but not all persons benefit from web-based interventions. Therefore, it is important to identify whether someone is likely to benefit from web-based PPIs, in order to triage persons who may not benefit from other interventions. In the current study, we used machine learning to predict individual response to a web-based PPI, in order to investigate baseline prognostic indicators of likelihood of response ( N = 120). Our models demonstrated moderate correlations (happiness: r Test = 0.30 ± 0.09; depressive symptoms: r Test = 0.39 ± 0.06), indicating that baseline features can predict changes in happiness and depressive symptoms at a 6-month follow-up. Thus, machine learning can be used to predict outcome changes from a web-based PPI and has important clinical implications for matching individuals to PPIs based on their individual characteristics., Competing Interests: Disclosure Statement The authors report there are no competing interests to declare.

Major Depressive Disorder (MDD) presents considerable challenges to diagnosis and management due to symptom variability across time. Only recent work has highlighted the clinical implications for interrogating depression symptom variability. Thus, the present work investigates how sociodemographic, comorbidity, movement, and sleep data is associated with long-term depression symptom variability. Participant information included (N = 939) baseline sociodemographic and comorbidity data, longitudinal, passively collected wearable data, and Patient Health Questionnaire-9 (PHQ-9) scores collected over 12 months. An ensemble machine learning approach was used to detect long-term depression symptom variability via: (i) a domain-driven feature selection approach and (ii) an exhaustive feature-inclusion approach. SHapley Additive exPlanations (SHAP) were used to interrogate variable importance and directionality. The composite domain-driven and exhaustive inclusion models were both capable of moderately detecting long-term depression symptom variability (r = 0.33 and r = 0.39, respectively). Our results indicate the incremental predictive validity of sociodemographic, comorbidity, and passively collected wearable movement and sleep data in detecting long-term depression symptom variability., (© 2023. The Author(s).)

Wearable technology enables unobtrusive collection of longitudinally dense data, allowing for continuous monitoring of physiology and behavior. These digital phenotypes, or device-based indicators, are frequently leveraged to study depression. However, they are usually considered alongside questionnaire sum-scores which collapse the symptomatic gamut into a general representation of severity. To explore the contributions of passive sensing streams more precisely, associations of nine passive sensing-derived features with self-report responses to Center for Epidemiologic Studies Depression (CES-D) items were modeled. Using data from the NetHealth study on N=469 college students, this work generated mixed ordinal logistic regression models to summarize contributions of pulse, movement, and sleep data to depression symptom detection. Emphasizing the importance of the college context, wearable features displayed unique and complementary properties in their heterogeneously significant associations with CES-D items. This work provides conceptual and exploratory blueprints for a reductionist approach to modeling depression within passive sensing research., Competing Interests: Declaration of competing interest None, (Copyright © 2023 Elsevier Ltd. All rights reserved.)

LCIA (low CO2-inducible protein A) is a chloroplast envelope protein associated with the CO2-concentrating mechanism of the green alga Chlamydomonas reinhardtii. LCIA is postulated to be a HCO3- channel, but previous studies were unable to show that LCIA was actively transporting bicarbonate in planta. Therefore, LCIA activity was investigated more directly in two heterologous systems: an Escherichia coli mutant (DCAKO) lacking both native carbonic anhydrases and an Arabidopsis mutant (βca5) missing the plastid carbonic anhydrase βCA5. Neither DCAKO nor βca5 can grow in ambient CO2 conditions, as they lack carbonic anhydrase-catalyzed production of the necessary HCO3- concentration for lipid and nucleic acid biosynthesis. Expression of LCIA restored growth in both systems in ambient CO2 conditions, which strongly suggests that LCIA is facilitating HCO3- uptake in each system. To our knowledge, this is the first direct evidence that LCIA moves HCO3- across membranes in bacteria and plants. Furthermore, the βca5 plant bioassay used in this study is the first system for testing HCO3- transport activity in planta, an experimental breakthrough that will be valuable for future studies aimed at improving the photosynthetic efficiency of crop plants using components from algal CO2-concentrating mechanisms., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Anxiety disorders are a prevalent and severe problem that are often developed early in life and can disrupt the daily lives of affected individuals for many years into adulthood. Given the persistent negative aspects of anxiety, accurate and early assessment is critical for long term outcomes. Currently, the most common method for anxiety assessment is through point-in-time measures like the GAD-7. Unfortunately, this survey and others like it can be subject to recall bias and do not fully capture the variability in an individual's day-to-day symptom experience. The current work aims to evaluate how point-in-time assessments like the GAD-7 relate to daily measurements of anxiety in a teenage population., Methods: To evaluate this relationship, we leveraged data collected at four separate three week intervals from 30 teenagers (age 15-17) over the course of a year. The specific items of interest were a single item anxiety severity measure collected three times per day and end-of-month GAD-7 assessments. Within this sample, 40 % of individuals reported clinical levels of generalized anxiety disorder symptoms at some point during the study. The first component of analysis was a visual inspection assessing how daily anxiety severity fluctuated around end-of-month reporting via the GAD-7. The second component was a between-subjects comparison assessing whether individuals with similar GAD-7 scores experienced similar symptom dynamics across the month as represented by latent features derived from a deep learning model. With this approach, similarity was operationalized by hierarchical clustering of the latent features., Results: The aim clearly indicated that an individual's daily experience of anxiety varied widely around what was captured by the GAD-7. Additionally, when hierarchical clustering was applied to the three latent features derived from the (LSTM) encoder (r = 0.624 for feature reconstruction), it was clear that individuals with similar GAD-7 outcomes were experiencing different symptom dynamics. Upon further inspection of the latent features, the LSTM model appeared to rely as much on anxiety variability over the course of the month as it did on anxiety severity (p < 0.05 for both mean and RMSSD) to represent an individual's experience., Discussion: This work serves as further evidence for the heterogeneity within the experience of anxiety and that more than just point-in-time assessments are necessary to fully capture an individual's experience., Competing Interests: Conflict of interest The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. This research is supported in part by T32 (T32DA037202-07) and P30 (P30DA029926) grants provided by the National Institute on Drug Abuse., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Carboxysomes are bacterial microcompartments, whose structural features enable the encapsulated Rubisco holoenzyme to operate in a high-CO 2 environment. Consequently, Rubiscos housed within these compartments possess higher catalytic turnover rates relative to their plant counterparts. This particular enzymatic property has made the carboxysome, along with associated transporters, an attractive prospect to incorporate into plant chloroplasts to increase future crop yields. To date, two carboxysome types have been characterized, the α-type that has fewer shell components and the β-type that houses a faster Rubisco. While research is underway to construct a native carboxysome in planta, work investigating the internal arrangement of carboxysomes has identified conserved Rubisco amino acid residues between the two carboxysome types which could be engineered to produce a new, hybrid carboxysome. In theory, this hybrid carboxysome would benefit from the simpler α-carboxysome shell architecture while simultaneously exploiting the higher Rubisco turnover rates in β-carboxysomes. Here, we demonstrate in an Escherichia coli expression system, that the Thermosynechococcus elongatus Form IB Rubisco can be imperfectly incorporated into simplified Cyanobium α-carboxysome-like structures. While encapsulation of non-native cargo can be achieved, T. elongatus Form IB Rubisco does not interact with the Cyanobium carbonic anhydrase, a core requirement for proper carboxysome functionality. Together, these results suggest a way forward to hybrid carboxysome formation., (© 2023. The Author(s).)

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (A c ) and electron transport-limited (A j ) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C 3 wheat and C 4 sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing A c alone generate more consistent but smaller yield gains across all water and nitrogen environments, A j enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both A c and A j generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross-scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research., (© 2022 The Authors. Plant, Cell & Environment published by John Wiley & Sons Ltd.)

Introduction: Schizophrenia and Major Depressive Disorder (MDD) are highly burdensome mental disorders, with significant cost to both individuals and society. Despite these disorders representing distinct clinical categories, they are each heterogenous in their symptom profiles, with considerable transdiagnostic features. Although movement and sleep abnormalities exist in both disorders, little is known of the precise nature of these changes longitudinally. Passively-collected longitudinal data from wearable sensors is well suited to characterize naturalistic features which may cross traditional diagnostic categories (e.g., highlighting behavioral markers not captured by self-report information)., Methods: The present analyses utilized raw minute-level actigraphy data from three diagnostic groups: individuals with schizophrenia (N = 23), individuals with depression (N = 22), and controls (N = 32), respectively, to interrogate naturalistic behavioral differences between groups. Subjects' week-long actigraphy data was processed without diagnostic labels via unsupervised machine learning clustering methods, in order to investigate the natural bounds of psychopathology. Further, actigraphic data was analyzed across time to determine timepoints influential in model outcomes., Results: We find distinct actigraphic phenotypes, which differ between diagnostic groups, suggesting that unsupervised clustering of naturalistic data aligns with existing diagnostic constructs. Further, we found statistically significant inter-group differences, with depressed persons showing the highest behavioral variability., Limitations: However, diagnostic group differences only consider biobehavioral trends captured by raw actigraphy information., Conclusions: Passively-collected movement information combined with unsupervised deep learning algorithms shows promise in identifying naturalistic phenotypes in individuals with mental health disorders, specifically in discriminating between MDD and schizophrenia., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Introduction: Despite existing work examining the effectiveness of smartphone digital interventions for schizophrenia at the group level, response to digital treatments is highly variable and requires more research to determine which persons are most likely to benefit from a digital intervention., Materials and Methods: The current work utilized data from an open trial of patients with psychosis ( N = 38), primarily schizophrenia spectrum disorders, who were treated with a psychosocial intervention using a smartphone app over a one-month period. Using an ensemble of machine learning models, pre-intervention data, app use data, and semi-structured interview data were utilized to predict response to change in symptom scores, engagement patterns, and qualitative impressions of the app., Results: Machine learning models were capable of moderately ( r = 0.32-0.39, R 2 = 0.10-0.16, MAE norm = 0.13-0.29) predicting interaction and experience with the app, as well as changes in psychosis-related psychopathology., Conclusion: The results suggest that individual smartphone digital intervention engagement is heterogeneous, and symptom-specific baseline data may be predictive of increased engagement and positive qualitative impressions of digital intervention in patients with psychosis. Taken together, interrogating individual response to and engagement with digital-based intervention with machine learning provides increased insight to otherwise ignored nuances of treatment response., Competing Interests: 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., (Copyright © 2022 Price, Heinz, Nemesure, McFadden and Jacobson.)

Importance: Selective serotonin reuptake inhibitors (SSRIs) are a common first-line treatment for some psychiatric disorders, including depression and anxiety; although they are generally well tolerated, SSRIs have known adverse effects, including movement problems, sleep disruption, and gastrointestinal problems (eg, nausea and upset stomach). No large-scale studies using naturalistic, longitudinal, objective data have validated physical activity findings, and actigraphy data are well suited to address this task., Objectives: To evaluate whether differences in physical movement exist among individuals treated with SSRIs compared with control participants and to identify the unique features of the movement of patients treated with SSRIs., Design, Setting, and Participants: This cross-sectional study examines longitudinally collected wearable movement data within a cross-sectional sample of 7162 participants from the 2005-2006 National Health and Nutrition Examination Survey (NHANES), a nationally representative population-based sample of noninstitutionalized persons in the US having both medication information and passive movement data. Statistical analysis was performed from April 1, 2021, to February 1, 2022., Exposures: The use of SSRIs (sertraline hydrochloride, escitalopram oxalate, fluoxetine hydrochloride, paroxetine hydrochloride, and citalopram hydrobromide), as reported by participants interviewed by NNHANES personnel, was the primary exposure, measured as a binary variable (taking an SSRI vs not taking an SSRI)., Main Outcomes and Measures: The primary outcome was the intensity of body movement as recorded by a piezoelectric accelerometer worn on the right hip for more than 1 week., Results: Of the 7162 participants included in the study, the mean (SD) age was 33.7 (22.6) years, 266 (3.7%) were taking an SSRI, 3706 (51.7%) were female, 1934 (27.0%) were Black, 1823 (25.5%) were Mexican American, 210 (2.9%) were other Hispanic, 336 (4.7%) were other or multiracial, and 2859 (39.9%) were White (per the NHANES data collection protocol). A cross-validated, deep learning classifier was constructed that achieved fair performance predicting SSRI use (area under the curve, 0.67 [95% CI, 0.64-0.71] for the validation set and 0.66 [95% CI, 0.64-0.68] for the test set). To account for possible confounding by indication, we constructed a parallel model incorporating depression severity, finding only marginal performance improvement. When averaged across individuals and across 7 days, the results show less overall movement in the SSRI group (mean, 120.1 vertical acceleration counts/min [95% CI, 115.7-124.6 vertical acceleration counts/min]) compared with the non-SSRI control group (mean, 168.8 vertical acceleration counts/min [95% CI, 162.8-174.9 vertical acceleration counts/min])., Conclusions and Relevance: This cross-sectional study found a moderate association between passive movement and SSRI use, as well as SSRI detection capacity of passive movement using time series deep learning models. The results support the use of passive sensors for exploration and characterization of psychotropic medication adverse effects.

Intro: As smartphone usage becomes increasingly prevalent in the workplace, the physical and psychological implications of this behavior warrant consideration. Recent research has investigated associations between workplace smartphone use and fatigue and boredom, yet findings are not conclusive., Methods: To build off recent efforts, we applied an ensemble machine learning model on a previously published dataset of N = 83 graduate students in the Netherlands to predict work boredom and fatigue from passively collected smartphone app use information. Using time-based feature engineering and lagged variations of the data to train, validate, and test idiographic models, we evaluated the efficacy of a lagged-ensemble predictive paradigm on sparse temporal data. Moreover, we probed the relative importance of both derived app use variables and lags within this predictive framework., Results: The ability to predict fatigue and boredom trajectories from app use information was heterogeneous and highly person-specific. Idiographic modeling reflected moderate to high correlative capacity ( r > 0.4) in 47% of participants for fatigue and 24% for boredom, with better overall performance in the fatigue prediction task. App use relating to duration, communication, and patterns of use frequency were among the most important features driving predictions across lags, with longer lags contributing more heavily to final ensemble predictions compared with shorter ones., Conclusion: A lag- specific ensemble predictive paradigm is a promising approach to leveraging high-dimensional app use behavioral data for the prediction of work fatigue and boredom. Future research will benefit from evaluating associations on densely collected data across longer time scales.

Background: The digital era has ushered in an unprecedented volume of readily accessible information, including news coverage of current events. Research has shown that the sentiment of news articles can evoke emotional responses from readers on a daily basis with specific evidence for increased anxiety and depression in response to coverage of the recent COVID-19 pandemic. Given the primacy and relevance of such information exposure, its daily impact on the mental health of the general population within this modality warrants further nuanced investigation., Objective: Using the COVID-19 pandemic as a subject-specific example, this work aimed to profile and examine associations between the dynamics of semantic affect in online local news headlines and same-day online mental health term search behavior over time across the United States., Methods: Using COVID-19-related news headlines from a database of online news stories in conjunction with mental health-related online search data from Google Trends, this paper first explored the statistical and qualitative affective properties of state-specific COVID-19 news coverage across the United States from January 23, 2020, to October 22, 2020. The resultant operationalizations and findings from the joint application of dictionary-based sentiment analysis and the circumplex theory of affect informed the construction of subsequent hypothesis-driven mixed effects models. Daily state-specific counts of mental health search queries were regressed on circumplex-derived features of semantic affect, time, and state (as a random effect) to model the associations between the dynamics of news affect and search behavior throughout the pandemic. Search terms were also grouped into depression symptoms, anxiety symptoms, and nonspecific depression and anxiety symptoms to model the broad impact of news coverage on mental health., Results: Exploratory efforts revealed patterns in day-to-day news headline affect variation across the first 9 months of the pandemic. In addition, circumplex mapping of the most frequently used words in state-specific headlines uncovered time-agnostic similarities and differences across the United States, including the ubiquitous use of negatively valenced and strongly arousing language. Subsequent mixed effects modeling implicated increased consistency in affective tone (Spin VA β=-.207; P<.001) as predictive of increased depression-related search term activity, with emotional language patterns indicative of affective uncontrollability (Flux A β=.221; P<.001) contributing generally to an increase in online mental health search term frequency., Conclusions: This study demonstrated promise in applying the circumplex model of affect to written content and provided a practical example for how circumplex theory can be integrated with sentiment analysis techniques to interrogate mental health-related associations. The findings from pandemic-specific news headlines highlighted arousal, flux, and spin as potentially significant affect-based foci for further study. Future efforts may also benefit from more expansive sentiment analysis approaches to more broadly test the practical application and theoretical capabilities of the circumplex model of affect on text-based data., (©Damien Lekkas, Joseph A Gyorda, George D Price, Zoe Wortzman, Nicholas C Jacobson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.01.2022.)

The carboxysome is a versatile paradigm of prokaryotic organelles and is a proteinaceous self-assembling microcompartment that plays essential roles in carbon fixation in all cyanobacteria and some chemoautotrophs. The carboxysome encapsulates the central CO 2 -fixing enzyme, ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), using a polyhedral protein shell that is selectively permeable to specific metabolites in favor of Rubisco carboxylation. There is tremendous interest in repurposing carboxysomes to boost carbon fixation in heterologous organisms. Here, we develop the design and engineering of α-carboxysomes by coexpressing the Rubisco activase components CbbQ and CbbO with α-carboxysomes in Escherichia coli . Our results show that CbbQ and CbbO could assemble into the reconstituted α-carboxysome as intrinsic components. Incorporation of both CbbQ and CbbO within the carboxysome promotes activation of Rubisco and enhances the CO 2 -fixation activities of recombinant carboxysomes. We also show that the structural composition of these carboxysomes could be modified in different expression systems, representing the plasticity of the carboxysome architecture. In translational terms, our study informs strategies for engineering and modulating carboxysomes in diverse biotechnological applications.

The uptake of inorganic carbon in cyanobacteria is facilitated by an energetically intensive CO 2 -concentrating mechanism (CCM). This includes specialized Type-1 NDH complexes that function to couple photosynthetic redox energy to CO 2 hydration forming the bicarbonate that accumulates to high cytoplasmic concentrations during the operation of the CCM, required for effective carbon fixation. Here we used a Synechococcus PCC7942 expression system to investigate the role of conserved histidine and cysteine residues in the CupB (also designated, ChpX) protein, which has been hypothesized to participate in a vectoral CO 2 hydration reaction near the interface between CupB protein and the proton-pumping subunits of the NDH-1 complex. A homology model has been constructed and most of the targeted conserved residues are in the vicinity of a Zn ion modeled to form the catalytic site of deprotonation and CO 2 hydration. Growth and CO 2 uptake assays show that the most severe defects in activity among the targeted residues are due to a substitution of the predicted Zn ligand, CupB-His86. Mutations at other sites produced intermediate effects. Proteomic analysis revealed that some amino acid substitution mutations of CupB caused the induction of bicarbonate uptake proteins to a greater extent than complete deletion of CupB, despite growth under CO 2 -enriched conditions. The results are discussed in terms of hypotheses on the catalytic function of this unusual enzyme., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Understanding the Earth's climate system during past periods of high atmospheric CO 2 is crucial for forecasting climate change under anthropogenically-elevated CO 2 . The Mesozoic Era is believed to have coincided with a long-term Greenhouse climate, and many of our temperature reconstructions come from stable isotopes of marine biotic calcite, in particular from belemnites, an extinct group of molluscs with carbonate hard-parts. Yet, temperatures reconstructed from the oxygen isotope composition of belemnites are consistently colder than those derived from other temperature proxies, leading to large uncertainties around Mesozoic sea temperatures. Here we apply clumped isotope palaeothermometry to two distinct carbonate phases from exceptionally well-preserved belemnites in order to constrain their living habitat, and improve temperature reconstructions based on stable oxygen isotopes. We show that belemnites precipitated both aragonite and calcite in warm, open ocean surface waters, and demonstrate how previous low estimates of belemnite calcification temperatures has led to widespread underestimation of Mesozoic sea temperatures by ca. 12 °C, raising estimates of some of the lowest temperature estimates for the Jurassic period to values which approach modern mid-latitude sea surface temperatures. Our findings enable accurate recalculation of global Mesozoic belemnite temperatures, and will thus improve our understanding of Greenhouse climate dynamics., (© 2021. The Author(s).)

Heterologous synthesis of a biophysical CO 2 -concentrating mechanism (CCM) in plant chloroplasts offers significant potential to improve the photosynthetic efficiency of C 3 plants and could translate into substantial increases in crop yield. In organisms utilizing a biophysical CCM, this mechanism efficiently surrounds a high turnover rate Rubisco with elevated CO 2 concentrations to maximize carboxylation rates. A critical feature of both native biophysical CCMs and one engineered into a C 3 plant chloroplast is functional bicarbonate (HCO 3 - ) transporters and vectorial CO 2 -to-HCO 3 - converters. Engineering strategies aim to locate these transporters and conversion systems to the C 3 chloroplast, enabling elevation of HCO 3 - concentrations within the chloroplast stroma. Several CCM components have been identified in proteobacteria, cyanobacteria, and microalgae as likely candidates for this approach, yet their successful functional expression in C 3 plant chloroplasts remains elusive. Here, we discuss the challenges in expressing and regulating functional HCO 3 - transporter, and CO 2 -to-HCO 3 - converter candidates in chloroplast membranes as an essential step in engineering a biophysical CCM within plant chloroplasts. We highlight the broad technical and physiological concerns which must be considered in proposed engineering strategies, and present our current status of both knowledge and knowledge-gaps which will affect successful engineering outcomes., Competing Interests: 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., (Copyright © 2021 Rottet, Förster, Hee, Rourke, Price and Long.)

Photocatalysts able to trigger the production of singlet oxygen species are the topic of intense research efforts in organic synthesis. Yet, challenges still exist in improving their activity and optimizing their use. Herein, we exploited the benefits of plasmonic nanoparticles to boost the activity of such photocatalysts via an antenna effect in the visible range. We synthesized silica-coated silver nanoparticles (Ag@SiO 2 NPs), with silica shells which thicknesses ranged from 7 to 45 nm. We showed that they served as plasmonically active supports for tris(bipyridine)ruthenium(II), [Ru(bpy) 3 ] 2+ , and demonstrated an enhanced catalytic activity under white light-emitting diode (LED) irradiation for citronellol oxidation, a key step in the commercial production of rose oxide fragrance. A maximum enhancement of the plasmon-mediated reactivity of approximately 3-fold was observed with a 28 nm silica layer along with a 4-fold enhancement in the emission intensity of the photocatalyst. Using electron energy loss spectroscopy (EELS) and boundary element method simulations, we mapped the decay of the plasmonic signal around the Ag core and provided a rationale for the observed catalytic enhancement. This work provides a systematic analysis of the promising properties of plasmonic NPs used as catalysis-enhancing supports for common homogeneous photocatalysts and a framework for the successful design of such systems in the context of organic transformations.

Membraneless organelles containing the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) are a common feature of organisms utilizing CO 2 concentrating mechanisms to enhance photosynthetic carbon acquisition. In cyanobacteria and proteobacteria, the Rubisco condensate is encapsulated in a proteinaceous shell, collectively termed a carboxysome, while some algae and hornworts have evolved Rubisco condensates known as pyrenoids. In both cases, CO 2 fixation is enhanced compared with the free enzyme. Previous mathematical models have attributed the improved function of carboxysomes to the generation of elevated CO 2 within the organelle via a colocalized carbonic anhydrase (CA) and inwardly diffusing HCO 3 - , which have accumulated in the cytoplasm via dedicated transporters. Here, we present a concept in which we consider the net of two protons produced in every Rubisco carboxylase reaction. We evaluate this in a reaction-diffusion compartment model to investigate functional advantages these protons may provide Rubisco condensates and carboxysomes, prior to the evolution of HCO 3 - accumulation. Our model highlights that diffusional resistance to reaction species within a condensate allows Rubisco-derived protons to drive the conversion of HCO 3 - to CO 2 via colocalized CA, enhancing both condensate [CO 2 ] and Rubisco rate. Protonation of Rubisco substrate (RuBP) and product (phosphoglycerate) plays an important role in modulating internal pH and CO 2 generation. Application of the model to putative evolutionary ancestors, prior to contemporary cellular HCO 3 - accumulation, revealed photosynthetic enhancements along a logical sequence of advancements, via Rubisco condensation, to fully formed carboxysomes. Our model suggests that evolution of Rubisco condensation could be favored under low CO 2 and low light environments., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

The superfamily Alveolinoidea is a member of the Order Miliolida, and comprises three main families, the Alveolinidae, the Fabulariidae and the Rhapydioninidae. They are examples of Larger benthic foraminifera (LBF), which are single-celled organisms with specific characteristic endoskeletons. Alveolinoids are found globally from the Cretaceous to the present day, and are important biostratigraphic index fossils in shallow-marine carbonates. They are often associated with hydrocarbon reservoirs, and exhibit provincialism with characteristic genera often confined to one of the American, Tethyan or Indo-Pacific provinces. Previously, the systematic study of the global interrelationship between the various alveolinoid lineages has not been possible because of the absence of biostratigraphic correlation between the geographically scattered assemblages, and the scarcity of described material from the Indo-Pacific province. Here we use the literature and new material from the Americas, the French Alps, Iran, Tibet, India and South East Asia, coupled with the use of the planktonic foraminiferal zonal (PZ) correlation scheme to propose a comprehensive, global, systematic analysis of the biostratigraphic, phylogenetic and paleogeographic evolution of the alveolinoids. The alveolinoids originated in the Cretaceous in the Tethyan province. During a global sea-level low stand, a westward migration of some alveolinoids species to the Americas occurred, a behaviour previously reported in contemporaneous orbitolinid LBF. After the Cretaceous/Palaeogene (K-P) event, which saw the extinction of all Cretaceous alveolinoids, rare new forms of alveolinoids evolved again, first in the Americas and later independently in Tethys. As was found in previous studies of rotalid LBF, sea-level low stands in the Paleocene also allowed some alveolinoid forms to migrate, but this time in an eastward direction from the Americas to Tethys, and from Tethys on to the Indo-Pacific province. Alveolinoids still exist today ( Borelis and Alveolinella ), the former of which is cosmopolitan, while the latter is restricted to the Indo-Pacific province. Throughout their phylogenetic history, alveolinoids characteristically exhibit convergent evolution, with the repeated re-occurrence of certain morphological features. Understanding this propensity to homoplasy is essential in understanding and constructing the phylogenetic relationships within the alveolinoid superfamily., Competing Interests: The authors declare no conflicts of interest in connection to this article., (© 2021 The Authors.)

Surface temperature is a fundamental parameter of Earth's climate. Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous ∆ 47 and ∆ 48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.

The Northern Hemisphere dominates our knowledge of Mesozoic and Cenozoic fossilized tree resin (amber) with few findings from the high southern paleolatitudes of Southern Pangea and Southern Gondwana. Here we report new Pangean and Gondwana amber occurrences dating from ~230 to 40 Ma from Australia (Late Triassic and Paleogene of Tasmania; Late Cretaceous Gippsland Basin in Victoria; Paleocene and late middle Eocene of Victoria) and New Zealand (Late Cretaceous Chatham Islands). The Paleogene, richly fossiliferous deposits contain significant and diverse inclusions of arthropods, plants and fungi. These austral discoveries open six new windows to different but crucial intervals of the Mesozoic and early Cenozoic, providing the earliest occurrence(s) of some taxa in the modern fauna and flora giving new insights into the ecology and evolution of polar and subpolar terrestrial ecosystems.

Localized surface plasmon resonance (LSPR) is a physical phenomenon exhibited by nanoparticles of metals including coinage metals, alkali metals, aluminum, and some semiconductors which translates into electromagnetic, thermal, and chemical properties. In the past decade, LSPR has been taken advantage of in the context of catalysis. While plasmonic nanoparticles (PNPs) have been successfully applied toward enhancing catalysis of inorganic reactions such as water splitting, they have also demonstrated exciting performance in the catalysis of organic transformations with potential applications in synthesis of molecules from commodity to pharmaceutical compounds. The advantages of this approach include improved selectivity, enhanced reaction rates, and milder reaction conditions. This review provides the basics of LSPR theory, details the mechanisms at play in plasmon-enhanced nanocatalysis, sheds light onto such nanocatalyst design, and finally systematically presents the breadth of organic reactions hence catalyzed.

Cyanobacteria have evolved a suite of enzymes and inorganic carbon (C i ) transporters that improve photosynthetic performance by increasing the localized concentration of CO 2 around the primary CO 2 -fixating enzyme, Rubisco. This CO 2 -concentrating mechanism (CCM) is highly regulated, responds to illumination/darkness cycles, and allows cyanobacteria to thrive under limiting C i conditions. While the transcriptional control of CCM activity is well understood, less is known about how regulatory proteins might allosterically regulate C i transporters in response to changing conditions. Cyanobacterial sodium-dependent bicarbonate transporters (SbtAs) are inhibited by P II -like regulatory proteins (SbtBs), with the inhibitory effect being modulated by adenylnucleotides. Here, we used isothermal titration calorimetry to show that SbtB from Cyanobium sp. PCC7001 (SbtB7001) binds AMP, ADP, cAMP, and ATP with micromolar-range affinities. X-ray crystal structures of apo and nucleotide-bound SbtB7001 revealed that while AMP, ADP, and cAMP have little effect on the SbtB7001 structure, binding of ATP stabilizes the otherwise flexible T-loop, and that the flexible C-terminal C-loop adopts several distinct conformations. We also show that ATP binding affinity is increased 10-fold in the presence of Ca 2+ , and we present an X-ray crystal structure of Ca 2+ ATP:SbtB7001 that shows how this metal ion facilitates additional stabilizing interactions with the apex of the T-loop. We propose that the Ca 2+ ATP-induced conformational change observed in SbtB7001 is important for allosteric regulation of SbtA activity by SbtB and is consistent with changing adenylnucleotide levels in illumination/darkness cycles.

Members of the Larger Benthic Foraminiferal (LBF) family Orbitolinidae occurred from the Cretaceous to the Paleogene, however, they were most diverse during the mid-Cretaceous, and dominated the agglutinated LBF assemblages described from limestones of that period. Various orbitolinid species have been used to zone and date lithologies formed in the shallow, warm waters of the Aptian to the early Cenomanian, and many, sometimes inaccurate, generic and sub-generic nomenclatures have been proposed to differentiate the often-subtle morphological changes that orbitolinids exhibit over time. Also, until now, it has not been possible to develop an effective global overview of their evolution and environmental development because descriptions of specimens from Asia have been relatively rare. Following our recent study of over 1800 orbitolinid-rich thin sections of material from 13 outcrops of Langshan limestone, from the Southern Tibetan Plateau, and from the Barito Basin, South Kalimantan, Indonesia, it has been possible to compare the stratigraphic ranges of these orbitolinids with previously described Tethyan and American forms, based on the use of a planktonic zonal (PZ) scheme, itself tied to the most recent chronostratigraphic scale. This has allowed the reconstruction of the phylogenetic and paleogeographic evolution of the orbitolinids from their Valanginian origin in the Tethys. Although the Tethys remained the paleogeographic centre for the orbitolinids, it is inferred here for the first time that a bi-directional paleogeographic migration of some orbitolinid genera occurred from the Tethys to the Americas and also to the Western Pacific region. Our observations and dating suggest that global marine regressions in the Aptian were coincident with, and may well have facilitated, these orbitolinid transoceanic migrations. Migration stopped however after rising sea level in the early Albian appears to have again isolated these provinces from each other. Tectonic forces associated with the subduction of the Farallon Plate and further sea level raises led to the opening of the Western Interior Seaway in North America, which correlates with, and may have been the cause of, the middle Albian (top of PZ Albian 2) extinction of the American orbitolinids. The extinction of the orbitolinids revealed that the Western Pacific province was split into two sub-provinces, with extinction occurring at the end of the early Albian (top of PZ Albian 1) in the Northwest Pacific sub-province, and at the end of the Albian (top of PZ Albian 4) in the subprovince that is today South East Asia (on the margins and west of the Wallace Line). The final near extinction of the orbitolinids occurred at the end of the Cenomanian in the Tethyan province, which coincides with, and may have been caused by, global anoxic oceanic events that correlate with a near-peak Mesozoic eustatic sea level high-stand that led to the overall global collapse of the paleotropical reef ecosystem at that time., Competing Interests: The authors declare no conflicts of interest in connection to this article., (© 2019 The Authors.)

Cells use compartmentalization of enzymes as a strategy to regulate metabolic pathways and increase their efficiency 1 . The α- and β-carboxysomes of cyanobacteria contain ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco)-a complex of eight large (RbcL) and eight small (RbcS) subunits-and carbonic anhydrase 2-4 . As HCO 3 - can diffuse through the proteinaceous carboxysome shell but CO 2 cannot 5 , carbonic anhydrase generates high concentrations of CO 2 for carbon fixation by Rubisco 6 . The shell also prevents access to reducing agents, generating an oxidizing environment 7-9 . The formation of β-carboxysomes involves the aggregation of Rubisco by the protein CcmM 10 , which exists in two forms: full-length CcmM (M58 in Synechococcus elongatus PCC7942), which contains a carbonic anhydrase-like domain 8 followed by three Rubisco small subunit-like (SSUL) modules connected by flexible linkers; and M35, which lacks the carbonic anhydrase-like domain 11 . It has long been speculated that the SSUL modules interact with Rubisco by replacing RbcS 2-4 . Here we have reconstituted the Rubisco-CcmM complex and solved its structure. Contrary to expectation, the SSUL modules do not replace RbcS, but bind close to the equatorial region of Rubisco between RbcL dimers, linking Rubisco molecules and inducing phase separation into a liquid-like matrix. Disulfide bond formation in SSUL increases the network flexibility and is required for carboxysome function in vivo. Notably, the formation of the liquid-like condensate of Rubisco is mediated by dynamic interactions with the SSUL domains, rather than by low-complexity sequences, which typically mediate liquid-liquid phase separation in eukaryotes 12,13 . Indeed, within the pyrenoids of eukaryotic algae, the functional homologues of carboxysomes, Rubisco adopts a liquid-like state by interacting with the intrinsically disordered protein EPYC1 14 . Understanding carboxysome biogenesis will be important for efforts to engineer CO 2 -concentrating mechanisms in plants 15-19 .

A long-term strategy to enhance global crop photosynthesis and yield involves the introduction of cyanobacterial CO 2 -concentrating mechanisms (CCMs) into plant chloroplasts. Cyanobacterial CCMs enable relatively rapid CO 2 fixation by elevating intracellular inorganic carbon as bicarbonate, then concentrating it as CO 2 around the enzyme Rubisco in specialized protein micro-compartments called carboxysomes. To date, chloroplastic expression of carboxysomes has been elusive, requiring coordinated expression of almost a dozen proteins. Here we successfully produce simplified carboxysomes, isometric with those of the source organism Cyanobium, within tobacco chloroplasts. We replace the endogenous Rubisco large subunit gene with cyanobacterial Form-1A Rubisco large and small subunit genes, along with genes for two key α-carboxysome structural proteins. This minimal gene set produces carboxysomes, which encapsulate the introduced Rubisco and enable autotrophic growth at elevated CO 2 . This result demonstrates the formation of α-carboxysomes from a reduced gene set, informing the step-wise construction of fully functional α-carboxysomes in chloroplasts.

Growth and productivity in important crop plants is limited by the inefficiencies of the C3 photosynthetic pathway. Introducing CO2-concentrating mechanisms (CCMs) into C3 plants could overcome these limitations and lead to increased yields. Many unicellular microautotrophs, such as cyanobacteria and green algae, possess highly efficient biophysical CCMs that increase CO2 concentrations around the primary carboxylase enzyme, Rubisco, to enhance CO2 assimilation rates. Algal and cyanobacterial CCMs utilize distinct molecular components, but share several functional commonalities. Here we outline the recent progress and current challenges of engineering biophysical CCMs into C3 plants. We review the predicted requirements for a functional biophysical CCM based on current knowledge of cyanobacterial and algal CCMs, the molecular engineering tools and research pipelines required to translate our theoretical knowledge into practice, and the current challenges to achieving these goals., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The supply of inorganic carbon (Ci) at the site of fixation by Rubisco is a key parameter for efficient CO2 fixation in aquatic organisms including the green alga, Chlamydomonas reinhardtii. Chlamydomonas reinhardtii cells, when grown on limiting CO2, have a CO2-concentrating mechanism (CCM) that functions to concentrate CO2 at the site of Rubisco. Proteins thought to be involved in inorganic carbon uptake have been identified and localized to the plasma membrane or chloroplast envelope. However, current CCM models suggest that additional molecular components are involved in Ci uptake. In this study, the gene Cia8 was identified in an insertional mutagenesis screen and characterized. The protein encoded by Cia8 belongs to the sodium bile acid symporter subfamily. Transcript levels for this gene were significantly up-regulated when the cells were grown on low CO2. The cia8 mutant exhibited reduced growth and reduced affinity for Ci when grown in limiting CO2 conditions. Prediction programs localize this protein to the chloroplast. Ci uptake and the photosynthetic rate, particularly at high external pH, were reduced in the mutant. The results are consistent with the model that CIA8 is involved in Ci uptake in C. reinhardtii., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

To support photosynthetic CO2 fixation by Rubisco, the chloroplast must be fed with inorganic carbon in the form of CO2 or bicarbonate. However, the mechanisms allowing the rapid passage of this gas and this charged molecule through the bounding membranes of the chloroplast envelope are not yet completely elucidated. We describe here a method allowing us to measure the permeability of these two molecules through the chloroplast envelope using a membrane inlet mass spectrometer and 18O-labelled inorganic carbon. We established that the internal stromal carbonic anhydrase activity is not limiting for this technique, and precisely measured the chloroplast surface area and permeability values for CO2 and bicarbonate. This was performed on chloroplasts from several plant species, with values ranging from 2.3 × 10-4 m s-1 to 8 × 10-4 m s-1 permeability for CO2 and 1 × 10-8 m s-1 for bicarbonate. We were able to apply our method to chloroplasts from an Arabidopsis aquaporin mutant, and this showed that CO2 permeability was reduced 50% in the mutant compared with the wild-type reference., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

The Late Jurassic to Early Cretaceous interval represents a time of environmental upheaval and cataclysmic events, combined with disruptions to terrestrial and marine ecosystems. Historically, the Jurassic/Cretaceous (J/K) boundary was classified as one of eight mass extinctions. However, more recent research has largely overturned this view, revealing a much more complex pattern of biotic and abiotic dynamics than has previously been appreciated. Here, we present a synthesis of our current knowledge of Late Jurassic-Early Cretaceous events, focusing particularly on events closest to the J/K boundary. We find evidence for a combination of short-term catastrophic events, large-scale tectonic processes and environmental perturbations, and major clade interactions that led to a seemingly dramatic faunal and ecological turnover in both the marine and terrestrial realms. This is coupled with a great reduction in global biodiversity which might in part be explained by poor sampling. Very few groups appear to have been entirely resilient to this J/K boundary 'event', which hints at a 'cascade model' of ecosystem changes driving faunal dynamics. Within terrestrial ecosystems, larger, more-specialised organisms, such as saurischian dinosaurs, appear to have suffered the most. Medium-sized tetanuran theropods declined, and were replaced by larger-bodied groups, and basal eusauropods were replaced by neosauropod faunas. The ascent of paravian theropods is emphasised by escalated competition with contemporary pterosaur groups, culminating in the explosive radiation of birds, although the timing of this is obfuscated by biases in sampling. Smaller, more ecologically diverse terrestrial non-archosaurs, such as lissamphibians and mammaliaforms, were comparatively resilient to extinctions, instead documenting the origination of many extant groups around the J/K boundary. In the marine realm, extinctions were focused on low-latitude, shallow marine shelf-dwelling faunas, corresponding to a significant eustatic sea-level fall in the latest Jurassic. More mobile and ecologically plastic marine groups, such as ichthyosaurs, survived the boundary relatively unscathed. High rates of extinction and turnover in other macropredaceous marine groups, including plesiosaurs, are accompanied by the origin of most major lineages of extant sharks. Groups which occupied both marine and terrestrial ecosystems, including crocodylomorphs, document a selective extinction in shallow marine forms, whereas turtles appear to have diversified. These patterns suggest that different extinction selectivity and ecological processes were operating between marine and terrestrial ecosystems, which were ultimately important in determining the fates of many key groups, as well as the origins of many major extant lineages. We identify a series of potential abiotic candidates for driving these patterns, including multiple bolide impacts, several episodes of flood basalt eruptions, dramatic climate change, and major disruptions to oceanic systems. The J/K transition therefore, although not a mass extinction, represents an important transitional period in the co-evolutionary history of life on Earth., (© 2016 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.)

The late Permian mass extinction event was the largest biotic crisis of the Phanerozoic and has the longest recovery interval of any extinction event. It has been hypothesised that subsequent carbon isotope perturbations during the Early Triassic are associated with biotic crises that impeded benthic recovery. We test this hypothesis by undertaking the highest-resolution study yet made of the rock and fossil records of the entire Werfen Formation, Italy. Here, we show that elevated extinction rates were recorded not only in the Dienerian, as previously recognised, but also around the Smithian/Spathian boundary. Functional richness increases across the Smithian/Spathian boundary associated with elevated origination rates in the lower Spathian. The taxonomic and functional composition of benthic faunas only recorded two significant changes: (1) reduced heterogeneity in the Dienerian, and (2) and a faunal turnover across the Smithian/Spathian boundary. The elevated extinctions and compositional shifts in the Dienerian and across the Smithian/Spathian boundary are associated with a negative and positive isotope excursion, respectively, which supports the hypothesis that subsequent biotic crises are associated with carbon isotope shifts. The Spathian fauna represents a more advanced ecological state, not recognised in the previous members of the Werfen Formation, with increased habitat differentiation, a shift in the dominant modes of life, appearance of stenohaline taxa and the occupation of the erect and infaunal tiers. In addition to subsequent biotic crises delaying the recovery, therefore, persistent environmental stress limited the ecological complexity of benthic recovery prior to the Spathian.

Global population growth is projected to outpace plant-breeding improvements in major crop yields within decades. To ensure future food security, multiple creative efforts seek to overcome limitations to crop yield. Perhaps the greatest limitation to increased crop yield is photosynthetic inefficiency, particularly in C3 crop plants. Recently, great strides have been made toward crop improvement by researchers seeking to introduce the cyanobacterial CO2-concentrating mechanism (CCM) into plant chloroplasts. This strategy recognises the C3 chloroplast as lacking a CCM, and being a primordial cyanobacterium at its essence. Hence the collection of solute transporters, enzymes, and physical structures that make cyanobacterial CO2-fixation so efficient are viewed as a natural source of genetic material for C3 chloroplast improvement. Also we highlight recent outstanding research aimed toward the goal of introducing a cyanobacterial CCM into C3 chloroplasts and consider future research directions., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Interest in the production of carbon commodities from photosynthetically fixed CO2 has focused attention on cyanobacteria as a target for metabolic engineering and pathway investigation. We investigated the redirection of carbon flux in the model cyanobacterial species, Synechococcus elongatus PCC 7942, under nitrogen deprivation, for optimized production of the industrially desirable compound, pyruvate. Under nitrogen limited conditions, excess carbon is naturally stored as the multi-branched polysaccharide, glycogen, but a block in glycogen synthesis, via knockout mutation in the gene encoding ADP-glucose pyrophosphorylase (glgC), results in the accumulation of the organic acids, pyruvate and 2-oxoglutarate, as overflow excretions into the extracellular media. The ΔglgC strain, under 48 h of N-deprivation was shown to excrete pyruvate for the first time in this strain. Additionally, by increasing culture pH, to pH 10, it was possible to substantially elevate excretion of pyruvate, suggesting the involvement of an unknown substrate/proton symporter for export. The ΔglgC mutant was also engineered to express foreign transporters for glucose and sucrose, and then grown photomixotrophically with exogenous organic carbon supply, as added 5 mM glucose or sucrose during N- deprivation. Under these conditions we observed a fourfold increase in extracellular pyruvate excretion when glucose was added, and a smaller increase with added sucrose. Although the magnitude of pyruvate excretion did not correlate with the capacity of the ΔglgC strain for bicarbonate-dependent photosynthetic O2 evolution, or with light intensity, there was, however, a positive correlation observed between the density of the starter culture prior to N-deprivation and the final extracellular pyruvate concentration. The factors that contribute to enhancement of pyruvate excretion are discussed, as well as consideration of whether the source of carbon for pyruvate excretion might be derived from photosynthetic CO2 fixation or from remobilisation of existing carbon stores.

Most major crops used for human consumption are C3 plants, which yields are limited by photosynthetic inefficiency. To circumvent this, it has been proposed to implement the cyanobacterial CO2-concentrating mechanism (CCM), principally consisting of bicarbonate transporters and carboxysomes, into plant chloroplasts. As it is currently not possible to recover homoplasmic transplastomic monocots, foreign genes must be introduced in these plants via nuclear transformation. Consequently, it is paramount to ensure that resulting proteins reach the appropriate sub-cellular compartment, which for cyanobacterial transporters BicA and SbtA, is the chloroplast inner-envelope membrane (IEM). At present, targeting signals to redirect large transmembrane proteins from non-chloroplastic organisms to plant chloroplast envelopes are unknown. The goal of this study was to identify such signals, using agrobacteria-mediated transient expression and confocal microscopy to determine the sub-cellular localization of ∼37 GFP-tagged chimeras. Initially, fragments of chloroplast proteins known to target soluble cargos to the stroma were tested for their ability to redirect BicA, but they proved ineffective. Next, different N-terminal regions from Arabidopsis IEM transporters were tested. We demonstrated that the N-terminus of AtHP59, AtPLGG1 or AtNTT1 (92-115 amino acids), containing a cleavable chloroplast transit peptide (cTP) and a membrane protein leader (MPL), was sufficient to redirect BicA or SbtA to the chloroplast envelope. This constitutes the first evidence that nuclear-encoded transmembrane proteins from non-chloroplastic organisms can be targeted to the envelope of plant chloroplasts; a finding which represents an important advance in chloroplast engineering by opening up the door to further manipulation of the chloroplastic envelope.

Cyanobacterial HCO3(-) transporters BCT1, SbtA and BicA are important components of cyanobacterial CO2-concentration mechanisms. They also show potential in applications aimed at improving photosynthetic rates and yield when expressed in the chloroplasts of C3 crop species. The present study investigated the feasibility of using Escherichia coli to assess function of a range of SbtA and BicA transporters in a heterologous expression system, ultimately for selection of transporters suitable for chloroplast expression. Here, we demonstrate that six β-forms of SbtA are active in E. coli, although other tested bicarbonate transporters were inactive. The sbtA clones were derived from Synechococcus sp. WH5701, Cyanobium sp. PCC7001, Cyanobium sp. PCC6307, Synechococcus elongatus PCC7942, Synechocystis sp. PCC6803, and Synechococcus sp. PCC7002. The six SbtA homologs varied in bicarbonate uptake kinetics and sodium requirements in E. coli. In particular, SbtA from PCC7001 showed the lowest uptake affinity and highest flux rate and was capable of increasing the internal inorganic carbon pool by more than 8 mM relative to controls lacking transporters. Importantly, we were able to show that the SbtB protein (encoded by a companion gene near sbtA) binds to SbtA and suppresses bicarbonate uptake function of SbtA in E. coli, suggesting a role in post-translational regulation of SbtA, possibly as an inhibitor in the dark. This study established E. coli as a heterologous expression and analysis system for HCO3(-) transporters from cyanobacteria, and identified several SbtA transporters as useful for expression in the chloroplast inner envelope membranes of higher plants.