Aneuploidy Causes Non-genetic Individuality.

Phenotypic variability is a hallmark of diseases involving chromosome gains and losses, such as Down syndrome and cancer. Allelic variances have been thought to be the sole cause of this heterogeneity. Here, we systematically examine the consequences of gaining and losing single or multiple chromosomes to show that the aneuploid state causes non-genetic phenotypic variability. Yeast cell populations harboring the same defined aneuploidy exhibit heterogeneity in cell-cycle progression and response to environmental perturbations. Variability increases with degree of aneuploidy and is partly due to gene copy number imbalances, suggesting that subtle changes in gene expression impact the robustness of biological networks and cause alternate behaviors when they occur across many genes. As inbred trisomic mice also exhibit variable phenotypes, we further propose that non-genetic individuality is a universal characteristic of the aneuploid state that may contribute to variability in presentation and treatment responses of diseases caused by aneuploidy.

A chromatin-based mechanism for limiting divergent noncoding transcription.

In addition to their annotated transcript, many eukaryotic mRNA promoters produce divergent noncoding transcripts. To define determinants of divergent promoter directionality, we used genomic replacement experiments. Sequences within noncoding transcripts specified their degradation pathways, and functional protein-coding transcripts could be produced in the divergent direction. To screen for mutants affecting the ratio of transcription in each direction, a bidirectional fluorescent protein reporter construct was introduced into the yeast nonessential gene deletion collection. We identified chromatin assembly as an important regulator of divergent transcription. Mutations in the CAF-I complex caused genome-wide derepression of nascent divergent noncoding transcription. In opposition to the CAF-I chromatin assembly pathway, H3K56 hyperacetylation, together with the nucleosome remodeler SWI/SNF, facilitated divergent transcription by promoting rapid nucleosome turnover. We propose that these chromatin-mediated effects control divergent transcription initiation, complementing downstream pathways linked to early termination and degradation of the noncoding RNAs.

Profiling of ubiquitin-like modifications reveals features of mitotic control.

Ubiquitin and ubiquitin-like (Ubl) protein modifications affect protein stability, activity, and localization, but we still lack broad understanding of the functions of Ubl modifications. We have profiled the protein targets of ubiquitin and six additional Ubls in mitosis using a functional assay that utilizes active mammalian cell extracts and protein microarrays and identified 1,500 potential substrates; 80-200 protein targets were exclusive to each Ubl. The network structure is nonrandom, with most targets mapping to a single Ubl. There are distinct molecular functions for each Ubl, suggesting divergent biological roles. Analysis of differential profiles between mitosis and G1 highlighted a previously underappreciated role for the Ubl, FAT10, in mitotic regulation. In addition to its role as a resource for Ubl modifications, our study provides a systematic approach to analyze changes in posttranslational modifications at various cellular states.

Genetic redundancy: new tricks for old genes.

Many crucial components of signal transduction, developmental, and metabolic pathways have functionally redundant copies. Further, these redundancies show surprising evolutionary stability over prolonged time scales. We propose that redundancies are not just archeological leftovers of ancient gene duplications, but rather that synergy arising from feedback between redundant copies may serve as an information processing element that facilitates signal transduction and the control of gene expression.

Early Introduction and Rise of the Omicron Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variant in Highly Vaccinated University Populations.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible in vaccinated and unvaccinated populations. The dynamics that govern its establishment and propensity toward fixation (reaching 100% frequency in the SARS-CoV-2 population) in communities remain unknown. Here, we describe the dynamics of Omicron at 3 institutions of higher education (IHEs) in the greater Boston area. METHODS: We use diagnostic and variant-specifying molecular assays and epidemiological analytical approaches to describe the rapid dominance of Omicron following its introduction into 3 IHEs with asymptomatic surveillance programs. RESULTS: We show that the establishment of Omicron at IHEs precedes that of the state and region and that the time to fixation is shorter at IHEs (9.5-12.5 days) than in the state (14.8 days) or region. We show that the trajectory of Omicron fixation among university employees resembles that of students, with a 2- to 3-day delay. Finally, we compare cycle threshold values in Omicron vs Delta variant cases on college campuses and identify lower viral loads among college affiliates who harbor Omicron infections. CONCLUSIONS: We document the rapid takeover of the Omicron variant at IHEs, reaching near-fixation within the span of 9.5-12.5 days despite lower viral loads, on average, than the previously dominant Delta variant. These findings highlight the transmissibility of Omicron, its propensity to rapidly dominate small populations, and the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.

Computational analysis of GAL pathway pinpoints mechanisms underlying natural variation.

Quantitative traits are measurable phenotypes that show continuous variation over a wide phenotypic range. Enormous effort has recently been put into determining the genetic influences on a variety of quantitative traits with mixed success. We identified a quantitative trait in a tractable model system, the GAL pathway in yeast, which controls the uptake and metabolism of the sugar galactose. GAL pathway activation depends both on galactose concentration and on the concentrations of competing, preferred sugars such as glucose. Natural yeast isolates show substantial variation in the behavior of the pathway. All studied yeast strains exhibit bimodal responses relative to external galactose concentration, i.e. a set of galactose concentrations existed at which both GAL-induced and GAL-repressed subpopulations were observed. However, these concentrations differed in different strains. We built a mechanistic model of the GAL pathway and identified parameters that are plausible candidates for capturing the phenotypic features of a set of strains including standard lab strains, natural variants, and mutants. In silico perturbation of these parameters identified variation in the intracellular galactose sensor, Gal3p, the negative feedback node within the GAL regulatory network, Gal80p, and the hexose transporters, HXT, as the main sources of the bimodal range variation. We were able to switch the phenotype of individual yeast strains in silico by tuning parameters related to these three elements. Determining the basis for these behavioral differences may give insight into how the GAL pathway processes information, and into the evolution of nutrient metabolism preferences in different strains. More generally, our method of identifying the key parameters that explain phenotypic variation in this system should be generally applicable to other quantitative traits.

A Semi-Quantitative Isothermal Diagnostic Assay Utilizing Competitive Amplification.

Quantitative diagnostics that are rapid, inexpensive, sensitive, robust, and field-deployable are needed to contain the spread of infectious diseases and inform treatment strategies. While current gold-standard techniques are highly sensitive and quantitative, they are slow and require expensive equipment. Conversely, current rapid field-deployable assays available provide essentially binary information about the presence of the target analyte, not a quantitative measure of concentration. Here, we report the development of a molecular diagnostic test [quantitative recombinase polymerase amplification (qRPA)] that utilizes competitive amplification during a recombinase polymerase amplification (RPA) assay to provide semi-quantitative information on a target nucleic acid. We demonstrate that qRPA can quantify DNA, RNA, and viral titers in HIV and COVID-19 patient samples and that it is more robust to environmental perturbations than traditional RPA. These features make qRPA potentially useful for at-home testing to monitor the progress of viral infections or other diseases.

Computational study on ratio-sensing in yeast galactose utilization pathway.

Metabolic networks undergo gene expression regulation in response to external nutrient signals. In microbes, the synthesis of enzymes that are used to transport and catabolize less preferred carbon sources is repressed in the presence of a preferred carbon source. For most microbes, glucose is a preferred carbon source, and it has long been believed that as long as glucose is present in the environment, the expression of genes related to the metabolism of alternative carbon sources is shut down, due to catabolite repression. However, recent studies have shown that the induction of the galactose (GAL) metabolic network does not solely depend on the exhaustion of glucose. Instead, the GAL genes respond to the external concentration ratio of galactose to glucose, a phenomenon of unknown mechanism that we termed ratio-sensing. Using mathematical modeling, we found that ratio-sensing is a general phenomenon that can arise from competition between two carbon sources for shared transporters, between transcription factors for binding to communal regulatory sequences of the target genes, or a combination of the aforementioned two levels of competition. We analyzed how the parameters describing the competitive interaction influenced ratio-sensing behaviors in each scenario and found that the concatenation of both layers of signal integration could expand the dynamical range of ratio-sensing. Finally, we investigated the influence of circuit topology on ratio-sensing and found that incorporating negative auto-regulation and/or coherent feedforward loop motifs to the basic signal integration unit could tune the sensitivity of the response to the external nutrient signals. Our study not only deepened our understanding of how ratio-sensing is achieved in yeast GAL metabolic regulation, but also elucidated design principles for ratio-sensing signal processing that can be used in other biological settings, such as being introduced into circuit designs for synthetic biology applications.

Semi-automated measurement of vascular tortuosity and its implications for mechanical thrombectomy performance.

PURPOSE: Few studies have examined the geometry of endovascular mechanical thrombectomy pathways. Here we examine the tortuosity and angulations of catheter pathways from the aortic arch to the termination of the internal carotid artery (ICA) and its association with thrombectomy performance. METHODS: We included 100 consecutive anterior circulation large vessel occlusion thrombectomy patients over 12 months. Computed tomography angiograms (CTA) were used for 3D segmentation of catheter pathway from the aortic arch to ICA termination. Tortuosity index (TI) and angulations of the catheter pathway were measured in a semi-automated fashion. TI and angulation degree were compared between sides and correlated with age and procedural measures. RESULTS: We analyzed 188 catheter pathways in 100 patients. Severe angulation (≤ 30°) was present in 5.8% and 39.4% of common carotid artery (CCA) and extracranial ICA segments, respectively. Five pathways (2.6%) had 360° loop. CCA and extracranial ICA tortuosity had a weak but significant correlation with age (r = 0.17, 0.21, p value = 0.05, 0.02 respectively), time from groin puncture to the site of occlusion (r = 0.29, 0.25, p values = 0.008, 0.026 respectively), and fluoroscopy time (r = 0.022, 0.31, p values = 0.016, 0.001 respectively). There was a significant difference in the pattern of angulation (p value = 0.04) and tortuosity between right and left side in CCA segment (TI = 0.20 ± 0.086 vs. 0.15 ± 0.82, p value < 0.001). CONCLUSIONS: There was a significant difference in CCA angulation between right and left sides. TI of extracranial CCA and ICA correlated with age and influenced time from groin puncture to the occlusion site and total fluoroscopy time.

Polymorphisms in the yeast galactose sensor underlie a natural continuum of nutrient-decision phenotypes.

In nature, microbes often need to "decide" which of several available nutrients to utilize, a choice that depends on a cell's inherent preference and external nutrient levels. While natural environments can have mixtures of different nutrients, phenotypic variation in microbes' decisions of which nutrient to utilize is poorly studied. Here, we quantified differences in the concentration of glucose and galactose required to induce galactose-responsive (GAL) genes across 36 wild S. cerevisiae strains. Using bulk segregant analysis, we found that a locus containing the galactose sensor GAL3 was associated with differences in GAL signaling in eight different crosses. Using allele replacements, we confirmed that GAL3 is the major driver of GAL induction variation, and that GAL3 allelic variation alone can explain as much as 90% of the variation in GAL induction in a cross. The GAL3 variants we found modulate the diauxic lag, a selectable trait. These results suggest that ecological constraints on the galactose pathway may have led to variation in a single protein, allowing cells to quantitatively tune their response to nutrient changes in the environment.

Assigning function to natural allelic variation via dynamic modeling of gene network induction.

More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be "personalized" according to the genotype, their variation may then reveal how DNA variants operate in the network. Here, we combined experiments and computations to visualize natural alleles of the yeast GAL3 gene in a space of model parameters describing the galactose response network. Alleles altering the activation of Gal3p by galactose were discriminated from those affecting its activity (production/degradation or efficiency of the activated protein). The approach allowed us to correctly predict that a non-synonymous SNP would change the binding affinity of Gal3p with the Gal80p transcriptional repressor. Our results illustrate how personalizing gene regulatory models can be used for the mechanistic interpretation of genetic variants.

Total RNA-seq to identify pharmacological effects on specific stages of mRNA synthesis.

Pharmacological perturbation is a powerful tool for understanding mRNA synthesis, but identification of the specific steps of this multi-step process that are targeted by small molecules remains challenging. Here we applied strand-specific total RNA sequencing (RNA-seq) to identify and distinguish specific pharmacological effects on transcription and pre-mRNA processing in human cells. We found unexpectedly that the natural product isoginkgetin, previously described as a splicing inhibitor, inhibits transcription elongation. Compared to well-characterized elongation inhibitors that target CDK9, isoginkgetin caused RNA polymerase accumulation within a broader promoter-proximal band, indicating that elongation inhibition by isoginkgetin occurs after release from promoter-proximal pause. RNA-seq distinguished isoginkgetin and CDK9 inhibitors from topoisomerase I inhibition, which alters elongation across gene bodies. We were able to detect these and other specific defects in mRNA synthesis at low sequencing depth using simple metagene-based metrics. These metrics now enable total-RNA-seq-based screening for high-throughput identification of pharmacological effects on individual stages of mRNA synthesis.

Natural variation in preparation for nutrient depletion reveals a cost-benefit tradeoff.

Maximizing growth and survival in the face of a complex, time-varying environment is a common problem for single-celled organisms in the wild. When offered two different sugars as carbon sources, microorganisms first consume the preferred sugar, then undergo a transient growth delay, the "diauxic lag," while inducing genes to metabolize the less preferred sugar. This delay is commonly assumed to be an inevitable consequence of selection to maximize use of the preferred sugar. Contrary to this view, we found that many natural isolates of Saccharomyces cerevisiae display short or nonexistent diauxic lags when grown in mixtures of glucose (preferred) and galactose. These strains induce galactose utilization (GAL) genes hours before glucose exhaustion, thereby "preparing" for the transition from glucose to galactose metabolism. The extent of preparation varies across strains, and seems to be determined by the steady-state response of GAL genes to mixtures of glucose and galactose rather than by induction kinetics. Although early GAL gene induction gives strains a competitive advantage once glucose runs out, it comes at a cost while glucose is still present. Costs and benefits correlate with the degree of preparation: strains with higher expression of GAL genes prior to glucose exhaustion experience a larger upfront growth cost but also a shorter diauxic lag. Our results show that classical diauxic growth is only one extreme on a continuum of growth strategies constrained by a cost-benefit tradeoff. This type of continuum is likely to be common in nature, as similar tradeoffs can arise whenever cells evolve to use mixtures of nutrients.

Achieving global perfect homeostasis through transporter regulation.

Nutrient homeostasis-the maintenance of relatively constant internal nutrient concentrations in fluctuating external environments-is essential to the survival of most organisms. Transcriptional regulation of plasma membrane transporters by internal nutrient concentrations is typically assumed to be the main mechanism by which homeostasis is achieved. While this mechanism is homeostatic we show that it does not achieve global perfect homeostasis-a condition where internal nutrient concentrations are completely independent of external nutrient concentrations for all external nutrient concentrations. We show that the criterion for global perfect homeostasis is that transporter levels must be inversely proportional to net nutrient flux into the cell and that downregulation of active transporters (activity-dependent regulation) is a simple and biologically plausible mechanism that meets this criterion. Activity-dependent transporter regulation creates a trade-off between robustness and efficiency, i.e., the system's ability to withstand perturbation in external nutrients and the transporter production rate needed to maintain homeostasis. Additionally, we show that a system that utilizes both activity-dependent transporter downregulation and regulation of transporter synthesis by internal nutrient levels can create a system that mitigates the shortcomings of each of the individual mechanisms. This analysis highlights the utility of activity-dependent regulation in achieving homeostasis and calls for a re-examination of the mechanisms of regulation of other homeostatic systems.

Galactose metabolic genes in yeast respond to a ratio of galactose and glucose.

Natural environments are filled with multiple, often competing, signals. In contrast, biological systems are often studied in "well-controlled" environments where only a single input is varied, potentially missing important interactions between signals. Catabolite repression of galactose by glucose is one of the best-studied eukaryotic signal integration systems. In this system, it is believed that galactose metabolic (GAL) genes are induced only when glucose levels drop below a threshold. In contrast, we show that GAL gene induction occurs at a constant external galactose:glucose ratio across a wide range of sugar concentrations. We systematically perturbed the components of the canonical galactose/glucose signaling pathways and found that these components do not account for ratio sensing. Instead we provide evidence that ratio sensing occurs upstream of the canonical signaling pathway and results from the competitive binding of the two sugars to hexose transporters. We show that a mutant that behaves as the classical model expects (i.e., cannot use galactose above a glucose threshold) has a fitness disadvantage compared with wild type. A number of common biological signaling motifs can give rise to ratio sensing, typically through negative interactions between opposing signaling molecules. We therefore suspect that this previously unidentified nutrient sensing paradigm may be common and overlooked in biology.

Abundance-based classifier for the prediction of mass spectrometric peptide detectability upon enrichment (PPA).

The function of a large percentage of proteins is modulated by post-translational modifications (PTMs). Currently, mass spectrometry (MS) is the only proteome-wide technology that can identify PTMs. Unfortunately, the inability to detect a PTM by MS is not proof that the modification is not present. The detectability of peptides varies significantly making MS potentially blind to a large fraction of peptides. Learning from published algorithms that generally focus on predicting the most detectable peptides we developed a tool that incorporates protein abundance into the peptide prediction algorithm with the aim to determine the detectability of every peptide within a protein. We tested our tool, "Peptide Prediction with Abundance" (PPA), on in-house acquired as well as published data sets from other groups acquired on different instrument platforms. Incorporation of protein abundance into the prediction allows us to assess not only the detectability of all peptides but also whether a peptide of interest is likely to become detectable upon enrichment. We validated the ability of our tool to predict changes in protein detectability with a dilution series of 31 purified proteins at several different concentrations. PPA predicted the concentration dependent peptide detectability in 78% of the cases correctly, demonstrating its utility for predicting the protein enrichment needed to observe a peptide of interest in targeted experiments. This is especially important in the analysis of PTMs. PPA is available as a web-based or executable package that can work with generally applicable defaults or retrained from a pilot MS data set.

The quantitative methods boot camp: teaching quantitative thinking and computing skills to graduate students in the life sciences.

The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a "boot camp" in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students' engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.

Mutations in LYRM4, encoding iron-sulfur cluster biogenesis factor ISD11, cause deficiency of multiple respiratory chain complexes.

Iron-sulfur clusters (ISCs) are important prosthetic groups that define the functions of many proteins. Proteins with ISCs (called iron-sulfur or Fe-S proteins) are present in mitochondria, the cytosol, the endoplasmic reticulum and the nucleus. They participate in various biological pathways including oxidative phosphorylation (OXPHOS), the citric acid cycle, iron homeostasis, heme biosynthesis and DNA repair. Here, we report a homozygous mutation in LYRM4 in two patients with combined OXPHOS deficiency. LYRM4 encodes the ISD11 protein, which forms a complex with, and stabilizes, the sulfur donor NFS1. The homozygous mutation (c.203G>T, p.R68L) was identified via massively parallel sequencing of >1000 mitochondrial genes (MitoExome sequencing) in a patient with deficiency of complexes I, II and III in muscle and liver. These three complexes contain ISCs. Sanger sequencing identified the same mutation in his similarly affected cousin, who had a more severe phenotype and died while a neonate. Complex IV was also deficient in her skeletal muscle. Several other Fe-S proteins were also affected in both patients, including the aconitases and ferrochelatase. Mutant ISD11 only partially complemented for an ISD11 deletion in yeast. Our in vitro studies showed that the l-cysteine desulfurase activity of NFS1 was barely present when co-expressed with mutant ISD11. Our findings are consistent with a defect in the early step of ISC assembly affecting a broad variety of Fe-S proteins. The differences in biochemical and clinical features between the two patients may relate to limited availability of cysteine in the newborn period and suggest a potential approach to therapy.

LanTERN: A Fluorescent Sensor That Specifically Responds to Lanthanides.

Lanthanides, a series of 15 f-block elements, are crucial in modern technology, and their purification by conventional chemical means comes at a significant environmental cost. Synthetic biology offers promising solutions. However, progress in developing synthetic biology approaches is bottlenecked because it is challenging to measure lanthanide binding with current biochemical tools. Here we introduce LanTERN, a lanthanide-responsive fluorescent protein. LanTERN was designed based on GCaMP, a genetically encoded calcium indicator that couples the ion binding of four EF hand motifs to increased GFP fluorescence. We engineered eight mutations across the parent construct's four EF hand motifs to switch specificity from calcium to lanthanides. The resulting protein, LanTERN, directly converts the binding of 10 measured lanthanides to 14-fold or greater increased fluorescence. LanTERN development opens new avenues for creating improved lanthanide-binding proteins and biosensing systems.