Pathway Usage Research Articles

Challenges of Spatially Resolved Metabolism in Cancer Research.

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

Chromatin context-dependent effects of epigenetic drugs on CRISPR-Cas9 editing.

The efficiency and outcome of CRISPR/Cas9 editing depends on the chromatin state at the cut site. It has been shown that changing the chromatin state can influence both the efficiency and repair outcome, and epigenetic drugs have been used to improve Cas9 editing. However, because the target proteins of these drugs are not homogeneously distributed across the genome, the efficacy of these drugs may be expected to vary from locus to locus. Here, we systematically analyzed this chromatin context-dependency for 160 epigenetic drugs. We used a human cell line with 19 stably integrated reporters to induce a double-stranded break in different chromatin environments. We then measured Cas9 editing efficiency and repair pathway usage by sequencing the mutational signatures. We identified 58 drugs that modulate Cas9 editing efficiency and/or repair outcome dependent on the local chromatin environment. For example, we find a subset of histone deacetylase inhibitors that improve Cas9 editing efficiency throughout all types of heterochromatin (e.g. PCI-24781), while others were only effective in euchromatin and H3K27me3-marked regions (e.g. apicidin). In summary, this study reveals that most epigenetic drugs alter CRISPR editing in a chromatin-dependent manner, and provides a resource to improve Cas9 editing more selectively at the desired location.

Rad51 determines pathway usage in post-replication repair.

Stalled replication forks can be processed by several distinct mechanisms collectively called post-replication repair which includes homologous recombination, fork regression, and translesion DNA synthesis. However, the regulation of the usage between these pathways is not fully understood. The Rad51 protein plays a pivotal role in maintaining genomic stability through its roles in HR and in protecting stalled replication forks from degradation. We report the isolation of separation-of-function mutations in Saccharomyces cerevisiae Rad51 that retain their recombination function but display a defect in fork protection leading to a shift in post-replication repair pathway usage from HR to alternate pathways including mutagenic translesion synthesis. Rad51-E135D and Rad51-K305N show normal in vivo and in vitro recombination despite changes in their DNA binding profiles, in particular to dsDNA, with a resulting effect on their ATPase activities. The mutants lead to a defect in Rad51 recruitment to stalled forks in vivo as well as a defect in the protection of dsDNA from degradation by Dna2-Sgs1 and Exo1 in vitro . A high-resolution cryo-electron microscopy structure of the Rad51-ssDNA filament at 2.4 Å resolution provides a structural basis for a mechanistic understanding of the mutant phenotypes. Together, the evidence suggests a model in which Rad51 binding to duplex DNA is critical to control pathway usage at stalled replication forks.

Improving routine use of clinical pathway decision support through integration of an EHR with a clinical library resource designed to provide evidence-based guidance within oncology workflows

BackgroundThe rapid evolution, complexity, and specialization of oncology treatment makes it challenging for physicians to provide care based on the latest and best evidence. We hypothesized that physicians would use evidence-based trusted care pathways if they were easy to use and integrated into clinical workflow at the point of care.MethodsWithin a large integrated care delivery system, we assembled clinical experts to define and update drug treatment pathways, encoded them as flowcharts in an online library integrated with the electronic medical record, communicated expectations that clinicians would use these pathways for every eligible patient, and combined data from multiple sources to understand usage over time.ResultsWe were able to achieve > 75% utilization of eligible protocols ordered through these pathways within two years, with > 90% of individual oncologists having consulted the pathway at least once, despite no requirements or external incentives associated with pathway usage. Feedback from users contributed to improvements and updates to the guidance.ConclusionsBy making our clinical decision support easily accessible and actionable, we find that we have made considerable progress toward our goal of having physicians consult the latest evidence in their treatment decisions.

Cell type-specific adaptation of the SARS-CoV-2 spike.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can infect various human tissues and cell types, principally via interaction with its cognate receptor angiotensin-converting enzyme-2 (ACE2). However, how the virus evolves in different cellular environments is poorly understood. Here, we used experimental evolution to study the adaptation of the SARS-CoV-2 spike to four human cell lines expressing different levels of key entry factors. After twenty passages of a spike-expressing recombinant vesicular stomatitis virus (VSV), cell-type-specific phenotypic changes were observed and sequencing allowed the identification of sixteen adaptive spike mutations. We used VSV pseudotyping to measure the entry efficiency, ACE2 affinity, spike processing, TMPRSS2 usage, and entry pathway usage of all the mutants, alone or in combination. The fusogenicity of the mutant spikes was assessed with a cell-cell fusion assay. Finally, mutant recombinant VSVs were used to measure the fitness advantage associated with selected mutations. We found that the effects of these mutations varied across cell types, both in terms of viral entry and replicative fitness. Interestingly, two spike mutations (L48S and A372T) that emerged in cells expressing low ACE2 levels increased receptor affinity, syncytia induction, and entry efficiency under low-ACE2 conditions. Our results demonstrate specific adaptation of the SARS-CoV-2 spike to different cell types and have implications for understanding SARS-CoV-2 tissue tropism and evolution.

3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data.

Fluorescence lifetime imaging of the co-enzyme reduced nicotinamide adenine dinucleotide (NADH) offers a label-free approach for detecting cellular metabolic perturbations. However, the relationships between variations in NADH lifetime and metabolic pathway changes are complex, preventing robust interpretation of NADH lifetime data relative to metabolic phenotypes. Here, a three-dimensional convolutional neural network (3D CNN) trained at the cell level with 3D NAD(P)H lifetime decay images (two spatial dimensions and one time dimension) was developed to identify metabolic pathway usage by cancer cells. NADH fluorescence lifetime images of MCF7 breast cancer cells with three isolated metabolic pathways, glycolysis, oxidative phosphorylation, and glutaminolysis were obtained by a multiphoton fluorescence lifetime microscope and then segmented into individual cells as the input data for the classification models. The 3D CNN models achieved over 90% accuracy in identifying cancer cells reliant on glycolysis, oxidative phosphorylation, or glutaminolysis. Furthermore, the model trained with human breast cancer cell data successfully predicted the differences in metabolic phenotypes of macrophages from control and POLG-mutated mice. These results suggest that the integration of autofluorescence lifetime imaging with 3D CNNs enables intracellular spatial patterns of NADH intensity and temporal dynamics of the lifetime decay to discriminate multiple metabolic phenotypes. Furthermore, the use of 3D CNNs to identify metabolic phenotypes from NADH fluorescence lifetime decay images eliminates the need for time- and expertise-demanding exponential decay fitting procedures. In summary, metabolic-prediction CNNs will enable live-cell and in vivo metabolic measurements with single-cell resolution, filling a current gap in metabolic measurement technologies.

The levels of p53 govern the hierarchy of DNA damage tolerance pathway usage.

It is well-established that, through canonical functions in transcription and DNA repair, the tumor suppressor p53 plays a central role in safeguarding cells from the consequences of DNA damage. Recent data retrieved in tumor and stem cells demonstrated that p53 also carries out non-canonical functions when interacting with the translesion synthesis (TLS) polymerase iota (POLι) at DNA replication forks. This protein complex triggers a DNA damage tolerance (DDT) mechanism controlling the DNA replication rate. Given that the levels of p53 trigger non-binary rheostat-like functions in response to stress or during differentiation, we explore the relevance of the p53 levels for its DDT functions at the fork. We show that subtle changes in p53 levels modulate the contribution of some DDT factors including POLι, POLη, POLζ, REV1, PCNA, PRIMPOL, HLTF and ZRANB3 to the DNA replication rate. Our results suggest that the levels of p53 are central to coordinate the balance between DDT pathways including (i) fork-deceleration by the ZRANB3-mediated fork reversal factor, (ii) POLι-p53-mediated fork-slowing, (iii) POLι- and POLη-mediated TLS and (iv) PRIMPOL-mediated fork-acceleration. Collectively, our study reveals the relevance of p53 protein levels for the DDT pathway choice in replicating cells.

Understanding the Degradation of Carbofuran in Agricultural Area: A Review of Fate, Metabolites, and Toxicity

Pesticides are commonly applied in agriculture to manage pests, parasites, weeds, and other crop diseases to maximise product output value and minimise or reduce yield losses. Pesticides are widely and indiscriminately used in crop production in most countries. Carbofuran is a highly toxic insecticide commonly used to protect crops in agricultural areas. Exposure to carbofuran can cause harmful effects on both the ecological environment and human health, particularly on non-target species such as birds and aquatic organisms. Carbofuran continues to be used, although it has been banned in some countries. This review paper highlights carbofuran usage, its residue, toxicity, and mechanisms of degradation pathways in water, soil, and food, especially in agriculture. It has been shown that hydrolysis, photolysis, and microbial degradation are the main pathways for carbofuran degradation. Carbofuran phenol is significantly less toxic than all photo-metabolites, while 3-ketocarbofuran and 3-hydroxycarbofuran are practically as harmful as the parent compound. Hence, more study is needed on degradation pathways that may thoroughly minimise the toxicity of this deadly pesticide.

Label-free spatially maintained measurements of metabolic phenotypes in cells.

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, autofluorescence lifetime imaging is combined with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90%-92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. Additionally, the model trained with the lifetime features of cancer cells could be transferred to autofluorescence lifetime images of T cells, with a prediction that 80% of activated T cells were glycolytic, and 97% of quiescent T cells were oxidative. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity.

Large-scale genetic and multi-omics analyses identify molecular pathways underlying dilated cardiomyopathy

Abstract Background Dilated cardiomyopathy (DCM) is a heart muscle disease that represents a major public health burden. While both common and rare genetic variants are known to affect DCM risk, previous genome-wide association studies (GWAS) have yielded only few loci and the molecular pathways underlying DCM remain largely unknown. Purpose We aimed to discover novel genetic loci for DCM by combining data from biobank and case-control studies, and by combining GWAS with multi-trait analyses. We also pursued multi-omics Mendelian randomization to nominate novel molecular pathways underlying DCM. Methods and results We first performed a GWAS of ICD-code defined DCM (N=1472 cases) from two large biobank datasets (UK Biobank and Mass General Brigham Biobank), and found good genetic correlation (rg=0.82, SE=0.22) and similar heritability estimates (h2=0.12, SE=0.03 vs. h2=0.14, SE=0.03) when compared with a previously published GWAS of recruited DCM cases. In a large meta-analysis across case-control and biobank datasets (N=4191 cases), we identified 10 loci significantly associated with DCM. We then integrated this novel meta-analysis into a multi-trait GWAS (MTAG) with MRI-derived left ventricular traits from the UK Biobank (LVEF and LVESV; N=36083), which yielded 44 lead variants at 36 significant loci. Novel loci overlap reported Mendelian cardiomyopathy genes (ACTN2, OBSCN, MYH7B), support previous mechanistic findings (HSPB8; heat shock protein family), and include genomic regions also arising from a recent GWAS of hypertrophic cardiomyopathy (notably, SVIL). We then performed Mendelian randomization analyses on the MTAG GWAS, using genetic instruments from published multi-omics datasets. Mendelian randomisation of the blood metabolome suggests potential causal roles for metabolites, notably those involved in the pentose phosphate pathway (ribitol; β=0.25, SE=0.04) and glycemic excursion (1,5-anhydroglucitol; β=0.08, SE=0.02). Analyses of the blood proteome suggest potential causal roles for several serum proteins, including proteins involved in redox balance (glutathione synthetase; β=-0.34, SE=0.05), mTORC1 signalling (LAMTOR3; β=0.08, SE=0.01), and the pentose phosphate pathway (G6PE; β=0.09, SE=0.02). Conclusion Our analyses link several new genomic regions with DCM, and implicate redox disbalance and alternative usage of (gluco)metabolic pathways as putative causal mechanisms of disease. Future functional studies could determine whether these represent actionable findings.

Cell-Type Specific Requirement of Glucose Catabolism in Erythropoiesis and Thymopoiesis

Glucose catabolism through glycolysis is central to cellular life. In glycolysis, pyruvate is converted to lactate by lactate dehydrogenase (LDH) or oxidized into the tricarboxylic acid (TCA) cycle via acetyl-CoA by pyruvate dehydrogenase (PDH). However, the two enzymes LDH and PDH required for completing glucose catabolism have never been ablated simultaneously in any tissue in vivo to test if glycolysis is required for cell survival and function. Ldha and Ldhb, the genes coding for LDH have not been ablated simultaneously in in the erythroid lineage to test if LDH plays a significant role in erythropoiesis. It is also unknown if erythoid progenitor cells, which unlike mature erythrocytes contain mitochondria, rely on LDH or are able to oxidize glucose via PDH to support erythroid development. To address these questions, we have generated conditional genetic knockouts (KO) of Ldha, Ldhb and PDH ( Pdha1) in the hematopoietic system to study the requirement of glucose catabolism in erythropoiesis. We observed that Ldha Δ/Δ and Ldha Δ/Δ;Ldhb Δ/Δ but not Ldhb Δ/Δmice had anemia, consistent with an essential role for LDHA in erythrocytes or erythropoiesis. Anemia was more severe in Ldha Δ/Δ;Pdha1 Δ mice as compared to Ldha Δ/Δ mice suggesting LDH and PDH are required in concert to maintain erythroid development in vivo. Ldha Δ/Δ mice accumulated CD71 +Ter119 + erythroid progenitors but Ldha Δ/Δ;Pdha1 Δ knockout mice had a significant decrease in this population. Moreover, there was a more pronounced expansion of upstream CD71 -Ter119 int and CD71 +Ter119 int cells in Ldha Δ/Δ;Pdha1 Δmice. This suggest that the accumulation of CD71 +Ter119 + cells in Ldha Δ/Δ mice is dependent on PDH and that the presence of either LDHA or PDH is required for the progression from CD71 +Ter119 int to CD71 +Ter119 + erythroid progenitors. The bone marrow of Ldha Δ/Δ;Pdha1 Δ showed an accumulation of pre-CFU-E and a depletion of CFU-E cells as compared to single Ldha Δ/Δ mice. Therefore, the presence of either LDHA or PDH is required to transit from pre-CFU-E to CFU-E stage during erythroid differentiation. Our previous results show that PDH is required for the double positive (DP) stage of T cell development. Analysis of thymus of Ldha Δ/Δ and Ldha Δ/Δ;Ldhb Δ/Δ mice did not show any changes in thymocytes. However, Ldha Δ/Δ;Pdha1 Δmice showed a significant decrease at the double negative (DN1) stage which persisted through all T cell development stages. Given that, PDH is required at the double positive (DP) stage and LDH deficiency alone does not affect T cell development, this suggest that LDH and PDH act redundantly at different stages to support T cell development. Altogether, these results suggest cell-type specific usage of glucose catabolic pathways in different differentiation stages. Our results also suggest that progenitor cells can switch between LDH and PDH for glucose catabolism while mature immune cells rely on either LDH or PDH for survival. To investigate this, we will use metabolomics and isotope tracing methods to analyze the route of glucose catabolism during erythroid and T cell development.

Remote nurse triage and standardization of clinical pathway utilization.

574 Background: In March of 2022, Texas Oncology (community oncology practice) initiated a state-wide rollout for Remote Nurse Triage. This program implemented and standardized the utilization of Clinical Pathways within the Navigating Care system with a goal to decrease time to patient first call back, increase first touch resolution for patient-initiated contact, and increase patient satisfaction related to patient-initiated communication resolution. Methods: To determine an appropriate plan of action, a needs assessment was conducted to evaluate current pathway utilization, call volumes and patient satisfaction. Based on the findings of this assessment, triage nurses were trained to resolve incidents using standardized care pathways and standing orders within the Navigating Care System. This implementation was monitored on a weekly basis with metrics from Navigating Care and the Relatient dashboard and compared to the 12-month baseline data for 2 beta sites. Results: In the 12-month pilot, standardized pathway utilization increased from 1% pre-pilot to 78% post-pilot for clinical symptom management calls. With standardized pathways and better first touch resolution clinical calls decreased 8% overall from 4,302/month to 3,987/month while patient volumes (billable visits) increased 25%. Patient satisfaction scores, in relation to their phone experience and needs resolution, went up to 4.5/5 from 3.9/5. Symptom management resolution times also trended down since beginning the pilot. Conclusions: Standardizing the usage of clinical pathways by virtual triage nurses reduced clinical call volumes despite a positive growth in the number of billable visits at the pilot sites. This increase in pathway utilization also led to decreased time for symptom management resolution. Additionally, these measures resulted in an increased patient satisfaction related to patient-initiated communication.

Conversion of Similar Xenochemicals to Dissimilar Products: Exploiting Competing Reactions in Whole-Cell Catalysis.

Many enzymes have latent activities that can be used in the conversion of non-natural reactants for novel organic conversions. A classic example is the conversion of benzaldehyde to a phenylacetyl carbinol, a precursor for ephedrine manufacture. It is often tacitly assumed that purified enzymes are more promising catalysts than whole cells, despite the lower cost and easier maintenance of the latter. Competing substrates inside the cell have been known to elicit currently hard-to-predict selectivities that are not easily measured inside the living cell. We employ NMR spectroscopic assays to rationally combine isomers for selective reactions in commercial S. cerevisiae. This approach uses internal competition between alternative pathways of aldehyde clearance in yeast, leading to altered selectivities compared to catalysis with the purified enzyme. In this manner, 4-fluorobenzyl alcohol and 2-fluorophenylacetyl carbinol can be formed with selectivities in the order of 90%. Modification of the cellular redox state can be used to tune product composition further. Hyperpolarized NMR shows that the cellular reaction and pathway usage are affected by the xenochemical. Overall, we find that the rational construction of ternary or more complex substrate mixtures can be used for in-cell NMR spectroscopy to optimize the upgrading of similar xenochemicals to dissimilar products with cheap whole-cell catalysts.

Uncovering transcriptomic landscape alterations of CAN-2409 in in vitro and in vivo glioma models.

CAN-2409 is a locally delivered oncolytic therapy, which results in vaccination against the injected tumor. CAN-2409 consists of a non-replicating adenovirus armed with the Herpes virus thymidine kinase, which metabolizes ganciclovir into a phosphorylated nucleotide that is incorporated into the tumor cell's genome, thereby inflicting immunogenic cancer cell death. While CAN-2409's immunological impact has been well characterized, its effects on the tumor cells transcriptome remains unknown. We compared the transcriptomic landscape after treatment of glioblastoma models with CAN-2409 in vitro and in vivo to assess how the interplay with the tumor microenvironment influences CAN-2409-mediated transcriptome alterations. We performed RNA-Seq with CAN-2409 treated patient-derived glioma stem-like cells and tumors of C57/BL6 mice and compared KEGG pathway usage and differential gene expression focusing on immune cell and cytokine profiles. T-cell -killing assays were performed to assess candidate effectors. PCA analysis showed distinct clustering of control and CAN-2409 samples under both conditions. KEGG pathway analysis revealed significant enrichment for p53 signaling and cell cycle pathway, with similar dynamics for key regulators of both pathways in vitro and in vivo, including MYC, CCNB1, PLK1 and CDC20. Selected alterations (PLK1 and CCNB1) were validated at the protein level. Cytokine expression analysis revealed upregulation of pro-inflammatory IL12a under both conditions; immune cell gene profiling showed reduction of myeloid associated genes. T-cell-killing assays showed increased killing in the presence of IL-12. CAN-2409 significantly alters the transcriptome both in vitro and in vivo. Comparison of pathway enrichment revealed mutual and differential utilization of pathways under both conditions, suggesting a modulating influence on the cell cycle in tumor cells, and of the tumor microenvironment on the transcriptome in vivo. IL-12 synthesis likely depends on interactions with the tumor microenvironment, and it facilitates CAN-2409 cell killing. This dataset provides potential to understand resistance mechanisms and identify potential biomarkers for future studies.

In-Cell NMR Approach for Real-Time Exploration of Pathway Versatility: Substrate Mixtures in Nonengineered Yeast.

The central carbon metabolism of microbes will likely be used in future sustainable bioproduction. A sufficiently deep understanding of central metabolism would advance the control of activity and selectivity in whole-cell catalysis. Opposite to the more obvious effects of adding catalysts through genetic engineering, the modulation of cellular chemistry through effectors and substrate mixtures remains less clear. NMR spectroscopy is uniquely suited for in-cell tracking to advance mechanistic insight and to optimize pathway usage. Using a comprehensive and self-consistent library of chemical shifts, hyperpolarized NMR, and conventional NMR, we probe the versatility of cellular pathways to changes in substrate composition. Conditions for glucose influx into a minor pathway to an industrial precursor (2,3-butanediol) can thus be designed. Changes to intracellular pH can be followed concurrently, while mechanistic details for the minor pathway can be derived using an intermediate-trapping strategy. Overflow at the pyruvate level can be induced in nonengineered yeast with suitably mixed carbon sources (here glucose with auxiliary pyruvate), thus increasing glucose conversion to 2,3-butanediol by more than 600-fold. Such versatility suggests that a reassessment of canonical metabolism may be warranted using in-cell spectroscopy.

The novel two-component system AmsSR governs alternative metabolic pathway usage in Acinetobacter baumannii.

In this study, we identify a novel two-component system in Acinetobacter baumannii (herein named AmsSR for regulator of alternative metabolic systems) only present in select gammaproteobacterial and betaproteobacterial species. Bioinformatic analysis revealed that the histidine kinase, AmsS, contains 14 predicted N-terminal transmembrane domains and harbors a hybrid histidine kinase arrangement in its C-terminus. Transcriptional analysis revealed the proton ionophore CCCP selectively induces P amsSR expression. Disruption of amsSR resulted in decreased intracellular pH and increased depolarization of cytoplasmic membranes. Transcriptome profiling revealed a major reordering of metabolic circuits upon amsR disruption, with energy generation pathways typically used by bacteria growing in limited oxygen being favored. Interestingly, we observed enhanced growth rates for mutant strains in the presence of glucose, which led to overproduction of pyruvate. To mitigate the toxic effects of carbon overflow, we noted acetate overproduction in amsSR-null strains, resulting from a hyperactive Pta-AckA pathway. Additionally, due to altered expression of key metabolic genes, amsSR mutants favor an incomplete TCA cycle, relying heavily on an overactive glyoxylate shunt. This metabolic reordering overproduces NADH, which is not oxidized by the ETC; components of which were significantly downregulated upon amsSR disruption. As a result, the mutants almost exclusively rely on substrate phosphorylation for ATP production, and consequently display reduced oxygen consumption in the presence of glucose. Collectively, our data suggests that disruption of amsSR affects the function of the aerobic respiratory chain, impacting the energy status of the cell, which in turn upregulates alternative metabolic and energy generation pathways.

Integration of physiologically relevant photosynthetic energy flows into whole genome models of light-driven metabolism.

Characterizing photosynthetic productivity is necessary to understand the ecological contributions and biotechnology potential of plants, algae, and cyanobacteria. Light capture efficiency and photophysiology have long been characterized by measurements of chlorophyll fluorescence dynamics. However, these investigations typically do not consider the metabolic network downstream of light harvesting. By contrast, genome-scale metabolic models capture species-specific metabolic capabilities but have yet to incorporate the rapid regulation of the light harvesting apparatus. Here, we combine chlorophyll fluorescence parameters defining photosynthetic and non-photosynthetic yield of absorbed light energy with a metabolic model of the pennate diatom Phaeodactylum tricornutum. This integration increases the model predictive accuracy regarding growth rate, intracellular oxygen production and consumption, and metabolic pathway usage. Through the quantification of excess electron transport, we uncover the sequential activation of non-radiative energy dissipation processes, cross-compartment electron shuttling, and non-photochemical quenching as the rapid photoacclimation strategy in P. tricornutum. Interestingly, the photon absorption thresholds that trigger the transition between these mechanisms were consistent at low and high incident photon fluxes. We use this understanding to explore engineering strategies for rerouting cellular resources and excess light energy towards bioproducts in silico. Overall, we present a methodology for incorporating a common, informative data type into computational models of light-driven metabolism and show its utilization within the design-build-test-learn cycle for engineering of photosynthetic organisms.

From fluorescent foci to sequence: Illuminating DNA double strand break repair by high-throughput sequencing technologies

Technologies to study DNA double-strand break (DSB) repair have traditionally mostly relied on fluorescence read-outs, either by microscopy or flow cytometry. The advent of high throughput sequencing (HTS) has created fundamentally new opportunities to study the mechanisms underlying DSB repair. Here, we review the suite of HTS-based assays that are used to study three different aspects of DNA repair: detection of broken ends, protein recruitment and pathway usage. We highlight new opportunities that HTS technology offers towards a better understanding of the DSB repair process.

Alveolar macrophages in early stage COPD show functional deviations with properties of impaired immune activation.

Despite its high prevalence, the cellular and molecular mechanisms of chronic obstructive pulmonary disease (COPD) are far from being understood. Here, we determine disease-related changes in cellular and molecular compositions within the alveolar space and peripheral blood of a cohort of COPD patients and controls. Myeloid cells were the largest cellular compartment in the alveolar space with invading monocytes and proliferating macrophages elevated in COPD. Modeling cell-to-cell communication, signaling pathway usage, and transcription factor binding predicts TGF-β1 to be a major upstream regulator of transcriptional changes in alveolar macrophages of COPD patients. Functionally, macrophages in COPD showed reduced antigen presentation capacity, accumulation of cholesteryl ester, reduced cellular chemotaxis, and mitochondrial dysfunction, reminiscent of impaired immune activation.

Abstract 2522: Pathway and immune profile analysis of cyst-derived versus PanIN-derived pancreatic ductal adenocarcinomas

Abstract Introduction: Pancreatic cystic lesions (PCL) are common and a subset of mucinous cysts will transform into pancreatic ductal adenocarcinoma (PDAC). However, predicting which of these mucinous PCL may progress to PDAC and warrant surgery remains a clinical challenge. Moreover, identifying those clinically emergent mucinous PCL for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of a PCL to identify novel biomarkers. Methods: We leveraged data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project and analyzed 66 PDAC cases recruited to ORIEN from The Ohio State University Wexner Medical Center and Moffitt Cancer Center for which tumor whole transcriptome sequencing datasets were generated. We separated the cases based on whether a tumor had originated from a cystic lesion (n=16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway (n=50). We then performed differential expression and pathway analysis using both Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Down-weighted Genes (PADOG) algorithms. Based on the emerging importance of the immune landscape in PDAC development, we also analyzed immune profiles using a novel tool, Tumor-immune Microenvironment Deconvolution Web-portal for Bulk Transcriptomics (TIMEx). Results: When grouped by tumor origin, cyst-derived PDAC gene expression sets are enriched in immune signaling pathways, specifically NOTCH signaling (p=0.04), and demonstrate significant downregulation in amino acid metabolism, mitochondrial import and Gsα signaling pathways. Furthermore, GSEA based on TIMEx signatures indicated that multiple immune cell-specific profiles had significant enrichment scores in either the cyst-derived (for example, plasma cell: normalized enrichment score=-1.53; p=0.007) or non-cyst-derived (for example, neutrophil: normalized enrichment score=2.24; p=0.0001) PDAC cohorts. Conclusions: Our data suggest that cyst-derived and non-cyst-derived PDACs differ by immune profile, enhanced NOTCH pathway usage and in the metabolic processing of multiple amino acids. These initial findings support future studies to assess the accuracy of risk stratifying PCLs based on their amino acid, metabolic, or immune profiles, and exploration into mechanisms to explain these findings. Citation Format: Margaret A. Park, Somashekar G. Krishna, Maria C. Genilo-Delgado, Kristyn Gumpper-Fedus, Darwin L. Conwell, Phil A. Hart, Mary E. Dillhoff, Maria F. Gomez, Toni L. Basinski, Aamir N. Dam, Jason B. Klapman, Jason B. Fleming, Mokenge Malafa, Amir Mohammadi, Barbara A. Centeno, Kun Jiang, Daniel Jeong, Dung-Tsa Chen, Mengyu Xie, Aik Choon Tan, Brooke L. Fridley, Jamie K. Teer, Zobeida Cruz-Monserrate, Jennifer B. Permuth. Pathway and immune profile analysis of cyst-derived versus PanIN-derived pancreatic ductal adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2522.