Isocost Lines Describe the Cellular Economy of Genetic Circuits

Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.United States. Air Force Office of Scientific Research (Grant FA9550-14-1-0060)United States. Defense Advanced Research Projects Agency (Contract W911NF-12-1-0540)National Institutes of Health (U.S.) (Grant P50 GM098792

A Validation Study of the Korean Version of SPAN

Purpose: The SPAN, which is acronym standing for its four components: Startle, Physiological arousal, Anger, and Numbness, is a short post-traumatic stress disorder (PTSD) screening scale. This study sought to develop and validate a Korean version of the SPAN (SPAN-K). Materials and Methods: Ninety-three PTSD patients (PTSD group), 73 patients with non-psychotic psychiatric disorders (psychiatric control group), and 88 healthy participants (normal control group) were recruited for this study. Participants completed a variety of psychiatric assessments including the SPAN-K, the Davidson Trauma Scale (DTS), the Clinician-Administered PTSD Scale (CAPS), and the State-Trait Anxiety Inventory (STAI). Results: Cronbach's alpha and test-retest reliability values for the SPAN-K were both 0.80. Mean SPAN-K scores were 10.06 for the PTSD group, 4.94 for the psychiatric control group, and 1.42 for the normal control group. With respect to concurrent validity, correlation coefficients were 0.87 for SPAN-K vs. CAPS total scores (p<0.001) and 0.86 for SPAN-K vs. DTS scores (p<0.001). Additionally, correlation coefficients were 0.31 and 0.42 for SPAN-K vs. STAI-S and STAI-T, respectively. Receiver operating characteristic analysis of SPAN-K showed good diagnostic accuracy with an area under the curve (AUC) of 0.87. The SPAN-K showed the highest efficiency at a cutoff score of 7, with a sensitivity of 0.83, a specificity of 0.81, positive predictive value (PPV) of 0.88, and negative predictive value (NPV) of 0.73. Conclusion: These results suggest that the SPAN-K had good psychometric properties and may be a useful instrument for rapid screening of PTSD patients.This study was supported by a grant of the Korean Academy of Anxiety Disorders, Korean Neuropsychiatric Association, and Korean Research Foundation (2006-2005152), Republic of Korea

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention

Genome evolution in structured systems

The evolution of a genome is shaped by spatial interactions at multiple scales. At the angstrom level, structural constraints on both RNA molecules and proteins contribute to the evolution of a gene sequence. Such optimized genes are weaved together in a particular order, out of a near-infinite number of combinations, to result in a genome. The fate of a genome is intricately linked to the evolutionary fate of its host organism; in turn, the fate of an organism is governed by where it resides in space. In this dissertation, I investigate how structure shapes the evolution of a gene, genome content, and pathogen populations residing in a diseased human lung. Chapter 1 provides a brief historical overview of population genetics in structured environments. I motivate why it is important to determine the migration rate of new alleles. Chapter 2 investigates how pathogens evolve within the structure of the cystic fibrosis lung. I find that migration rate and mutation rate are on similar timescales. Selection, rather than spatial isolation, maintains diversity within a pathogen population. Chapter 3 presents a new method to probe how codon choice is optimized throughout a gene. I find that codon choice is dictated by preference for particular RNA secondary structures, rather than intrinsic properties of a codon. Chapter 4 describes an ongoing study of how rapidly P. aeruginosa populations evolve in short-term infections. Preliminary results show that gene duplication events can sweep through a population in just 11 days. Chapter 5 introduces ideas for future directions. I pose questions regarding how pathogens evolve molecular mimicry that can trigger autoimmune disease in the human host, and how cancer-inducing inflammation might be detected from mutational signatures in the microbiome.Systems Biolog

Inexpensive multiplexed library preparation for megabase-sized genomes.

Whole-genome sequencing has become an indispensible tool of modern biology. However, the cost of sample preparation relative to the cost of sequencing remains high, especially for small genomes where the former is dominant. Here we present a protocol for rapid and inexpensive preparation of hundreds of multiplexed genomic libraries for Illumina sequencing. By carrying out the Nextera tagmentation reaction in small volumes, replacing costly reagents with cheaper equivalents, and omitting unnecessary steps, we achieve a cost of library preparation of $8 per sample, approximately 6 times cheaper than the standard Nextera XT protocol. Furthermore, our procedure takes less than 5 hours for 96 samples. Several hundred samples can then be pooled on the same HiSeq lane via custom barcodes. Our method will be useful for re-sequencing of microbial or viral genomes, including those from evolution experiments, genetic screens, and environmental samples, as well as for other sequencing applications including large amplicon, open chromosome, artificial chromosomes, and RNA sequencing

Global and local selection acting on the pathogen Stenotrophomonas maltophilia in the human lung

Bacterial populations diversify during infection into distinct subpopulations that coexist within the human body. Yet, it is unknown to what extent subpopulations adapt to location-specific selective pressures as they migrate and evolve across space. Here we identify bacterial genes under local and global selection by testing for spatial co-occurrence of adaptive mutations. We sequence 552 genomes of the pathogen Stenotrophomonas maltophilia across 23 sites of the lungs from a patient with cystic fibrosis. We show that although genetically close isolates colocalize in space, distant lineages with distinct phenotypes separated by adaptive mutations spread throughout the lung, suggesting global selective pressures. Yet, for one gene (a distant homologue of the merC gene implicated in metal resistance), mutations arising independently in two lineages colocalize in space, providing evidence for location-specific selection. Our work presents a general framework for understanding how selection acts upon a pathogen that colonizes and evolves across the complex environment of the human body

Joint single-cell measurements of nuclear proteins and RNA in vivo

Identifying gene-regulatory targets of nuclear proteins in tissues is a challenge. Here we describe intranuclear cellular indexing of transcriptomes and epitopes (inCITE-seq), a scalable method that measures multiplexed intranuclear protein levels and the transcriptome in parallel across thousands of nuclei, enabling joint analysis of transcription factor (TF) levels and gene expression in vivo. We apply inCITE-seq to characterize cell state-related changes upon pharmacological induction of neuronal activity in the mouse brain. Modeling gene expression as a linear combination of quantitative protein levels revealed genome-wide associations of each TF and recovered known gene targets. TF-associated genes were coexpressed as distinct modules that each reflected positive or negative TF levels, showing that our approach can disentangle relative putative contributions of TFs to gene expression and add interpretability to inferred gene networks. inCITE-seq can illuminate how combinations of nuclear proteins shape gene expression in native tissue contexts, with direct applications to solid or frozen tissues and clinical specimens