Starvation-Induced Changes to the Midgut Proteome and Neuropeptides in Manduca sexta.

Starvation is a complex physiological state that induces changes in protein expression to ensure survival. The insect midgut is sensitive to changes in dietary content as it is at the forefront of communicating information about incoming nutrients to the body via hormones. Therefore, a DIA proteomics approach was used to examine starvation physiology and, specifically, the role of midgut neuropeptide hormones in a representative lepidopteran, Manduca sexta. Proteomes were generated from midguts of M. sexta fourth-instar caterpillars, starved for 24 h and 48 h, and compared to fed controls. A total of 3047 proteins were identified, and 854 of these were significantly different in abundance. KEGG analysis revealed that metabolism pathways were less abundant in starved caterpillars, but oxidative phosphorylation proteins were more abundant. In addition, six neuropeptides or related signaling cascade proteins were detected. Particularly, neuropeptide F1 (NPF1) was significantly higher in abundance in starved larvae. A change in juvenile hormone-degrading enzymes was also detected during starvation. Overall, our results provide an exploration of the midgut response to starvation in M. sexta and validate DIA proteomics as a useful tool for quantifying insect midgut neuropeptide hormones.

SARS-CoV-2 superinfection in CD14+ monocytes with latent human cytomegalovirus (HCMV) promotes inflammatory cascade.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has posed significant challenges to global health. While much attention has been directed towards understanding the primary mechanisms of SARS-CoV-2 infection, emerging evidence suggests co-infections or superinfections with other viruses may contribute to increased morbidity and mortality, particularly in severe cases of COVID-19. Among viruses that have been reported in patients with SARS-CoV-2, seropositivity for Human cytomegalovirus (HCMV) is associated with increased COVID-19 risk and hospitalization. HCMV is a ubiquitous beta-herpesvirus with a seroprevalence of 60-90 % worldwide and one of the leading causes of mortality in immunocompromised individuals. The primary sites of latency for HCMV include CD14+ monocytes and CD34+ hematopoietic cells. In this study, we sought to investigate SARS-CoV-2 infection of CD14+ monocytes latently infected with HCMV. We demonstrate that CD14+ cells are susceptible and permissive to SARS-CoV-2 infection and detect subgenomic transcripts indicative of replication. To further investigate the molecular changes triggered by SARS-CoV-2 infection in HCMV-latent CD14+ monocytes, we conducted RNA sequencing coupled with bioinformatic differential gene analysis. The results revealed significant differences in cytokine-cytokine receptor interactions and inflammatory pathways in cells superinfected with replication-competent SARS-CoV-2 compared to the heat-inactivated and mock controls. Notably, there was a significant upregulation in transcripts associated with pro-inflammatory response factors and a decrease in anti-inflammatory factors. Taken together, these findings provide a basis for the heightened inflammatory response, offering potential avenues for targeted therapeutic interventions among HCMV-infected severe cases of COVID-19. SUMMARY: COVID-19 patients infected with secondary viruses have been associated with a higher prevalence of severe symptoms. Individuals seropositive for human cytomegalovirus (HCMV) infection are at an increased risk for severe COVID-19 disease and hospitalization. HCMV reactivation has been reported in severe COVID-19 cases with respiratory failure and could be the result of co-infection with SARS-CoV-2 and HCMV. In a cell culture model of superinfection, HCMV has previously been shown to increase infection of SARS-CoV-2 of epithelial cells by upregulating the human angiotensin-converting enzyme-2 (ACE2) receptor. In this study, we utilize CD14+ monocytes, a major cell type that harbors latent HCMV, to investigate co-infection of SARS-CoV-2 and HCMV. This study is a first step toward understanding the mechanism that may facilitate increased COVID-19 disease severity in patients infected with SARS-CoV-2 and HCMV.

Localizing unmapped sequences with families to validate the Telomere-to-Telomere assembly and identify new hotspots for genetic diversity.

Although it is ubiquitous in genomics, the current human reference genome (GRCh38) is incomplete: It is missing large sections of heterochromatic sequence, and as a singular, linear reference genome, it does not represent the full spectrum of human genetic diversity. To characterize gaps in GRCh38 and human genetic diversity, we developed an algorithm for sequence location approximation using nuclear families (ASLAN) to identify the region of origin of reads that do not align to GRCh38. Using unmapped reads and variant calls from whole-genome sequences (WGSs), ASLAN uses a maximum likelihood model to identify the most likely region of the genome that a subsequence belongs to given the distribution of the subsequence in the unmapped reads and phasings of families. Validating ASLAN on synthetic data and on reads from the alternative haplotypes in the decoy genome, ASLAN localizes >90% of 100-bp sequences with >92% accuracy and ∼1 Mb of resolution. We then ran ASLAN on 100-mers from unmapped reads from WGS from more than 700 families, and compared ASLAN localizations to alignment of the 100-mers to the recently released T2T-CHM13 assembly. We found that many unmapped reads in GRCh38 originate from telomeres and centromeres that are gaps in GRCh38. ASLAN localizations are in high concordance with T2T-CHM13 alignments, except in the centromeres of the acrocentric chromosomes. Comparing ASLAN localizations and T2T-CHM13 alignments, we identified sequences missing from T2T-CHM13 or sequences with high divergence from their aligned region in T2T-CHM13, highlighting new hotspots for genetic diversity.

Crush Injury and Simulated Flight Effects on Muscle Gene Expression in Female Mice.

BACKGROUND: Aeromedical evacuation provides critical care during long-distance transport of injured victims between medical facilities. Often, these victims sustain muscle trauma related to mechanical insults, such as crush. Understanding the effects of flight on injured muscle is important because the aircraft cabin represents an external environment with mild hypoxia-the cabin's altitude is 2,438 m instead of sea level. Because mild hypobaric hypoxia can alter gene expression in normal muscle and affect recovery patterns, it is beneficial to examine whether this type of hypoxia may also alter injury-related genes. OBJECTIVE: The objective of this study was to verify the hypothesis that differential gene expression occurs in response to mild hypobaric hypoxia exposure in crush-injured muscle during two early recovery (preregeneration stage) time points. METHODS: Twenty-four female mice were anesthetized, and the right gastrocnemius muscle underwent crush injury. Approximately 24 hours later, mice were exposed to normobaric normoxia or hypobaric hypoxia for 8-9 hours. After 32 or 48 hours of recovery, the mice were euthanized, and the right and left lateral gastrocnemius muscles were collected for microarray and bioinformatics analyses. RESULTS: The study hypothesis was verified. There were 353 highly upregulated, differentially expressed genes identified in the injured muscle compared to the uninjured muscle. Mid1 was upregulated in both pressure conditions regardless of injury status. There were 52 and 15 differentially expressed genes at 32 and 48 hours postinjury, respectively, in the hypobaric hypoxia-exposed, injured muscle compared to the normobaric normoxia-exposed, injured muscle. The macrophage gene Cd68 correlated with other leukocyte-related genes. DISCUSSION: These findings expand our understanding of the genetic changes that occur in muscle in response to a crush injury, including those related to the macrophage protein CD68. Nursing interventions addressing adequate functioning after crush muscle injury may need to consider the effects on Cd68 and its closely related genes. In addition, our results suggest a responsiveness of the gene Mid1 to flight-relevant hypobaric hypoxia. Changes in the expression of Mid1 may be appropriate in assessing the long-term health of flight crew members.

Class I HDAC inhibitors attenuate dexamethasone-induced muscle atrophy via increased protein kinase C (PKC) delta phosphorylation.

Skeletal muscle atrophy is defined by wasting or decrease in muscle mass owing to injury, aging, malnutrition, chronic disuse, or physical consequences of chronic illness. Under normal physiological conditions, a network of signal transduction pathways serves to balance muscle protein synthesis and proteolysis; however, metabolic shifts occur from protein synthesis to protein degradation that leads to a reduction in cross-sectional myofibers and can result in loss of skeletal muscle mass (atrophy) over time. Recent evidence highlights posttranslational modifications (PTMs) such as acetylation and phosphorylation in contractile dysfunction and muscle wasting. Indeed, histone deacetylase (HDAC) inhibitors have been shown to attenuate muscle atrophy and delay muscle damage in response to nutrient deprivation, in models of metabolic dysfunction and genetic models of muscle disease (e.g., muscle dystrophy). Despite our current understanding of lysine acetylation in muscle physiology, a role for HDACs in the regulation of muscle signal transduction remains a 'black box.' Using C2C12 myotubes stimulated with dexamethasone (Dex) as a model of muscle atrophy, we report that protein kinase C delta (PKCδ) phosphorylation decreased at threonine 505 (T505) and serine 643 (S643) in myotubes in response to muscle atrophy; these residues are important for PKCδ activity. Interestingly, PKCδ phosphorylation was restored/increased in myotubes treated with a pan-HDAC inhibitor or a class I selective HDAC inhibitor targeting HDACs1, -2, and - 3 in response to Dex. Moreover, we observed that Dex induced atrophy in skeletal muscle tissue in mice; this reduction in atrophy occurred rapidly, with weight loss noted by day 3 post-Dex and muscle weight loss noted by day 7. Similar to our findings in C2C12 myotubes, Dex attenuated phosphorylation of PKCδ at S643, while HDAC inhibition restored or increased PKCδ phosphorylation at both T505 and S643 in the tibialis anterior. Consistent with this hypothesis, we report that HDAC inhibition could not restore myotube size in response to Dex in the presence of a PKCδ inhibitor or when overexpressing a dominant negative PKCδ. Additionally, the overexpression of a constitutively active PKCδ prevented Dex-induced myotube atrophy. Combined, these data suggest that HDACs regulate muscle physiology via changes in intracellular signaling, namely PKCδ phosphorylation. Whether HDACs regulate PKCδ through canonical (e.g. gene-mediated regulation of phosphatases) or non-canonical (e.g. direct deacetylation of PKCδ to change phosphorylation states) mechanisms remain unclear and future research is needed to clarify this point.

Towards the generation of gnotobiotic larvae as a tool to investigate the influence of the microbiome on the development of the amphibian immune system.

The immune equilibrium model suggests that exposure to microbes during early life primes immune responses for pathogen exposure later in life. While recent studies using a range of gnotobiotic (germ-free) model organisms offer support for this theory, we currently lack a tractable model system for investigating the influence of the microbiome on immune system development. Here, we used an amphibian species (Xenopus laevis) to investigate the importance of the microbiome in larval development and susceptibility to infectious disease later in life. We found that experimental reductions of the microbiome during embryonic and larval stages effectively reduced microbial richness, diversity and altered community composition in tadpoles prior to metamorphosis. In addition, our antimicrobial treatments resulted in few negative effects on larval development, body condition, or survival to metamorphosis. However, contrary to our predictions, our antimicrobial treatments did not alter susceptibility to the lethal fungal pathogen Batrachochytrium dendrobatidis (Bd) in the adult life stage. While our treatments to reduce the microbiome during early development did not play a critical role in determining susceptibility to disease caused by Bd in X. laevis, they nevertheless indicate that developing a gnotobiotic amphibian model system may be highly useful for future immunological investigations. This article is part of the theme issue 'Amphibian immunity: stress, disease and ecoimmunology'.

Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation.

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.

Modeling Human Lung Cells Exposure to Wildfire Uncovers Aberrant lncRNAs Signature.

Emissions generated by wildfires are a growing threat to human health and are characterized by a unique chemical composition that is tightly dependent on geographic factors such as fuel type. Long noncoding RNAs (lncRNAs) are a class of RNA molecules proven to be critical to many biological processes, and their condition-specific expression patterns are emerging as prominent prognostic and diagnostic biomarkers for human disease. We utilized a new air-liquid interface (ALI) direct exposure system that we designed and validated in house to expose immortalized human tracheobronchial epithelial cells (AALE) to two unique wildfire smokes representative of geographic regions (Sierra Forest and Great Basin). We conducted an RNAseq analysis on the exposed cell cultures and proved through both principal component and differential expression analysis that each smoke has a unique effect on the LncRNA expression profiles of the exposed cells when compared to the control samples. Our study proves that there is a link between the geographic origin of wildfire smoke and the resulting LncRNA expression profile in exposed lung cells and also serves as a proof of concept for the in-house designed ALI exposure system. Our study serves as an introduction to the scientific community of how unique expression patterns of LncRNAs in patients with wildfire smoke-related disease can be utilized as prognostic and diagnostic tools, as the current roles of LncRNA expression profiles in wildfire smoke-related disease, other than this study, are completely uncharted.

Artificial gravity partially protects space-induced neurological deficits in Drosophila melanogaster.

Spaceflight poses risks to the central nervous system (CNS), and understanding neurological responses is important for future missions. We report CNS changes in Drosophila aboard the International Space Station in response to spaceflight microgravity (SFµg) and artificially simulated Earth gravity (SF1g) via inflight centrifugation as a countermeasure. While inflight behavioral analyses of SFµg exhibit increased activity, postflight analysis displays significant climbing defects, highlighting the sensitivity of behavior to altered gravity. Multi-omics analysis shows alterations in metabolic, oxidative stress and synaptic transmission pathways in both SFµg and SF1g; however, neurological changes immediately postflight, including neuronal loss, glial cell count alterations, oxidative damage, and apoptosis, are seen only in SFµg. Additionally, progressive neuronal loss and a glial phenotype in SF1g and SFµg brains, with pronounced phenotypes in SFµg, are seen upon acclimation to Earth conditions. Overall, our results indicate that artificial gravity partially protects the CNS from the adverse effects of spaceflight.

Characterization of Anopheles stephensi Odorant Receptor 8, an Abundant Component of the Mouthpart Chemosensory Transcriptome.

Several mosquito species within the genus Anopheles are vectors for human malaria, and the spread of this disease is driven by the propensity of certain species to feed preferentially on humans. The study of olfaction in mosquitoes is important to understand dynamics of host-seeking and host-selection; however, the majority of these studies focus on Anopheles gambiae or An. coluzzii, both vectors of malaria in Sub-Saharan Africa. Other malaria vectors may recognize different chemical cues from potential hosts; therefore, in this study, we investigated An. stephensi, the south Asian malaria mosquito. We specifically focused on the mouthparts (primarily the maxillary palp and labella) that have been much less investigated compared to the antennae but are also important for host-seeking. To provide a broad view of chemoreceptor expression, RNAseq was used to examine the transcriptomes from the mouthparts of host-seeking females, blood-fed females, and males. Notably, AsOr8 had a high transcript abundance in all transcriptomes and was, therefore, cloned and expressed in the Drosophila empty neuron system. This permitted characterization with a panel of odorants that were selected, in part, for their presence in the human odor profile. The responsiveness of AsOr8 to odorants was highly similar to An. gambiae Or8 (AgOr8), except for sulcatone, which was detected by AsOr8 but not AgOr8. Subtle differences in the receptor sensitivity to specific odorants may provide clues to species- or strain-specific approaches to host-seeking and host selection. Further exploration of the profile of An. stephensi chemosensory proteins may yield a better understanding of how different malaria vectors navigate host-finding and host-choice.

CPA: a web-based platform for consensus pathway analysis and interactive visualization.

In molecular biology and genetics, there is a large gap between the ease of data collection and our ability to extract knowledge from these data. Contributing to this gap is the fact that living organisms are complex systems whose emerging phenotypes are the results of multiple complex interactions taking place on various pathways. This demands powerful yet user-friendly pathway analysis tools to translate the now abundant high-throughput data into a better understanding of the underlying biological phenomena. Here we introduce Consensus Pathway Analysis (CPA), a web-based platform that allows researchers to (i) perform pathway analysis using eight established methods (GSEA, GSA, FGSEA, PADOG, Impact Analysis, ORA/Webgestalt, KS-test, Wilcox-test), (ii) perform meta-analysis of multiple datasets, (iii) combine methods and datasets to accurately identify the impacted pathways underlying the studied condition and (iv) interactively explore impacted pathways, and browse relationships between pathways and genes. The platform supports three types of input: (i) a list of differentially expressed genes, (ii) genes and fold changes and (iii) an expression matrix. It also allows users to import data from NCBI GEO. The CPA platform currently supports the analysis of multiple organisms using KEGG and Gene Ontology, and it is freely available at http://cpa.tinnguyen-lab.com.

RNA-Seq used to identify ipsdienone reductase (IDONER): A novel monoterpene carbon-carbon double bond reductase central to Ips confusus pheromone production.

The pinyon ips beetle, Ips confusus (LeConte) is a highly destructive pest in pine forests in western North America. When colonizing a new host tree, I. confusus beetles coordinate a mass attack to overcome the tree's defenses using aggregation pheromones. Ips confusus, as with other Ips spp. beetles, biosynthesize ipsdienol and ipsenol in a specific enantiomeric blend and ratio as aggregation pheromones. While several of the initial steps in the pheromone biosynthetic pathway have been well defined, the final steps were unknown. We used comparative RNA-Seq analysis between fed and unfed male I. confusus midgut tissue to identify candidate genes involved in pheromone biosynthesis. The 12,995 potentially unique transcripts showed a clear separation based on feeding state. Differential expression analysis identified gene groups that were tightly connected. This analysis identified all known pheromone biosynthetic genes and suggested a novel monoterpene double bond reductase, ipsdienone reductase (IDONER), with pheromone biosynthetic gene expression patterns. IDONER cDNA was cloned, expressed, and functionally characterized. The coding DNA sequence has an ORF of 1101 nt with a predicted translation product of 336 amino acids. The enzyme has a molecular weight of 36.7 kDa with conserved motifs of the medium chain dehydrogenases/reductase (MDR) superfamily in the leukotriene B4 dehydrogenases/reductases (LTB4R) family. Tagged recombinant protein was expressed and purified. Enzyme assays and GC/MS analysis showed IDONER catalyzed the reduction of ipsdienone to form ipsenone. This study shows that IDONER is a monoterpene double bond reductase involved in I. confusus pheromone biosynthesis.

Knowledge, Training, and Attitudes of Students and Speech-Language Pathologists About Providing Communication Services to Individuals Who Are Transgender.

Purpose Little is known about the professional knowledge, training, and attitudes of current and future speech-language pathologists (SLPs) toward serving people who are transgender. The purpose of this study was to understand the current climate of students and professionals in delivering voice and communications services to people who are transgender. An understanding of these areas is necessary to help practicing and aspiring SLPs work toward cultural competence in serving this population. Method A survey was completed by 386 speech-language pathology students and SLPs at three professional conferences. The survey assessed the professional and ethical knowledge, training experiences, and attitudes of the participants in relation to communication services for people who are transgender. Results In terms of professional knowledge, the majority of students and experienced SLP respondents agreed or strongly agreed (77.8%) that treating clients who are transgender was within the SLP scope of practice and was their ethical responsibility (82.2%). Regarding training, approximately 20% of survey respondents received training for working with people who are transgender, whereas approximately 8% of survey respondents reported having experience working with clients who are transgender. With respect to attitude, approximately 54% of survey respondents reported being comfortable treating clients who are transgender, and 37% of survey respondents reported they were likely to pursue training for treating clients who are transgender. Additional analyses were completed comparing students and experienced SLPs as well as the influence of geographic region. Discussion Students and SLPs were generally knowledgeable of professional guidelines and standards regarding serving people who are transgender. However, in this survey, very few clinicians indicated they had received training to serve this population. Recommendations to address this gap are discussed.

The common transcriptional subnetworks of the grape berry skin in the late stages of ripening.

BACKGROUND: Wine grapes are important economically in many countries around the world. Defining the optimum time for grape harvest is a major challenge to the grower and winemaker. Berry skins are an important source of flavor, color and other quality traits in the ripening stage. Senescent-like processes such as chloroplast disorganization and cell death characterize the late ripening stage. RESULTS: To better understand the molecular and physiological processes involved in the late stages of berry ripening, RNA-seq analysis of the skins of seven wine grape cultivars (Cabernet Franc, Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay, Sauvignon Blanc and Semillon) was performed. RNA-seq analysis identified approximately 2000 common differentially expressed genes for all seven cultivars across four different berry sugar levels (20 to 26 °Brix). Network analyses, both a posteriori (standard) and a priori (gene co-expression network analysis), were used to elucidate transcriptional subnetworks and hub genes associated with traits in the berry skins of the late stages of berry ripening. These independent approaches revealed genes involved in photosynthesis, catabolism, and nucleotide metabolism. The transcript abundance of most photosynthetic genes declined with increasing sugar levels in the berries. The transcript abundance of other processes increased such as nucleic acid metabolism, chromosome organization and lipid catabolism. Weighted gene co-expression network analysis (WGCNA) identified 64 gene modules that were organized into 12 subnetworks of three modules or more and six higher order gene subnetworks. Some gene subnetworks were highly correlated with sugar levels and some subnetworks were highly enriched in the chloroplast and nucleus. The petal R package was utilized independently to construct a true small-world and scale-free complex gene co-expression network model. A subnetwork of 216 genes with the highest connectivity was elucidated, consistent with the module results from WGCNA. Hub genes in these subnetworks were identified including numerous members of the core circadian clock, RNA splicing, proteolysis and chromosome organization. An integrated model was constructed linking light sensing with alternative splicing, chromosome remodeling and the circadian clock. CONCLUSIONS: A common set of differentially expressed genes and gene subnetworks from seven different cultivars were examined in the skin of the late stages of grapevine berry ripening. A densely connected gene subnetwork was elucidated involving a complex interaction of berry senescent processes (autophagy), catabolism, the circadian clock, RNA splicing, proteolysis and epigenetic regulation. Hypotheses were induced from these data sets involving sugar accumulation, light, autophagy, epigenetic regulation, and fruit development. This work provides a better understanding of berry development and the transcriptional processes involved in the late stages of ripening.

petal: Co-expression network modelling in R.

BACKGROUND: Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies, many life scientists are grasping for user-friendly methods and tools to examine biological components at the whole-systems level. Gene co-expression network analysis approaches are frequently used to successfully associate genes with biological processes and demonstrate great potential to gain further insights into the functionality of genes, thus becoming a standard approach in Systems Biology. Here the objective is to construct biologically meaningful and statistically strong co-expression networks, the identification of research dependent subnetworks, and the presentation of self-contained results. RESULTS: We introduce petal, a novel approach to generate gene co-expression network models based on experimental gene expression measures. petal focuses on statistical, mathematical, and biological characteristics of both, input data and output network models. Often over-looked issues of current co-expression analysis tools include the assumption of data normality, which is seldom the case for hight-throughput expression data obtained from RNA-seq technologies. petal does not assume data normality, making it a statistically appropriate method for RNA-seq data. Also, network models are rarely tested for their known typical architecture: scale-free and small-world. petal explicitly constructs networks based on both these characteristics, thereby generating biologically meaningful models. Furthermore, many network analysis tools require a number of user-defined input variables, these often require tuning and/or an understanding of the underlying algorithm; petal requires no user input other than experimental data. This allows for reproducible results, and simplifies the use of petal. Lastly, this approach is specifically designed for very large high-throughput datasets; this way, petal's network models represent as much of the entire system as possible to provide a whole-system approach. CONCLUSION: petal is a novel tool for generating co-expression network models of whole-genomics experiments. It is implemented in R and available as a library. Its application to several whole-genome experiments has generated novel meaningful results and has lead the way to new testing hypothesizes for further biological investigation.

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world.

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.