We propose differential principal component analysis (dPCA) for analyzing multiple ChIP- sequencing datasets to identify differential protein–DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein–DNA interactions.
Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed “CLIK” (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality...
Cell-to-cell variability in molecular, genetic, and physiological features is increasingly recognized as a critical feature of complex biological systems, including the brain. Although such variability has potential advantages in robustness and reliability, how and why biological circuits assemble heterogeneous cells into functional groups is poorly understood. Here, we develop analytic approaches toward answering how neuron-level variation in intrinsic biophysical properties of olfactory bulb mitral cells influences population coding of fluctuating stimuli. We capture the intrinsic diversity of recorded populations of neurons through a statistical approach based on generalized linear models. These models are flexible enough to predict the diverse responses of individual neurons yet provide a common reference frame for comparing one neuron to the next. We then use Bayesian stimulus decoding to ask how effectively different populations of mitral cells, varying in their diversity, encode a common stimulus. We show that a key advantage provided by physiological levels of intrinsic diversity is more efficient and more robust encoding of stimuli by the population as a whole. However, we find that the populations that best encode stimulus features are not simply the most heterogeneous...
Proton transfer across biological membranes underpins central processes in biological systems, such as energy conservation and transport of ions and molecules. In the membrane proteins involved in these processes, proton transfer takes place through specific pathways connecting the two sides of the membrane via control elements within the protein. It is commonly believed that acidic residues are required near the orifice of such proton pathways to facilitate proton uptake. In cytochrome c oxidase, one such pathway starts near a conserved Asp-132 residue. Results from earlier studies have shown that replacement of Asp-132 by, e.g., Asn, slows proton uptake by a factor of ∼5,000. Here, we show that proton uptake at full speed (∼104 s−1) can be restored in the Asp-132–Asn oxidase upon introduction of a second structural modification further inside the pathway (Asn-139–Thr) without compensating for the loss of the negative charge. This proton-uptake rate was insensitive to Zn2+ addition, which in the wild-type cytochrome c oxidase slows the reaction, indicating that Asp-132 is required for Zn2+ binding. Furthermore, in the absence of Asp-132 and with Thr at position 139, at high pH (>9), proton uptake was significantly accelerated. Thus...
Regulation of an intracellular acidic environment plays a pivotal role in biological processes and functions. However, spatiotemporal analysis of the acidification in complex tissues of living subjects persists as an important challenge. We developed a photo-inactivatable bioluminescent indicator, based on a combination of luciferase-fragment complementation and a photoreaction of a light, oxygen, and voltage domain from Avena sativa Phototropin1 (LOV2), to visualize temporally dynamic acidification in living tissue samples. Bioluminescence of the indicator diminished upon light irradiation and it recovered gradually in the dark state thereafter. The recovery rate was remarkably sensitive to pH changes but unsusceptible to fluctuation of luciferin or ATP concentrations. Bioluminescence imaging, taken as an index of the recovery rates, enabled long-time recording of acidification in apoptotic and autophagous processes in a cell population and an ischemic condition in living mice. This technology using the indicator is widely applicable to sense organelle-specific acidic changes in target biological tissues.
Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Toward this end, we used single-dimension ultra–high-pressure liquid chromatography mass spectrometry to investigate the comprehensive “intact” proteome of the Gram-negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1,665 proteoforms generated by posttranslational modifications (PTMs), representing the largest microbial top-down dataset reported to date. We confirmed many previously recognized aspects of Salmonella biology and bacterial PTMs, and our analysis also revealed several additional biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions. This finding of a S-glutathionylation-to-S-cysteinylation switch in a condition-specific manner was corroborated by bottom-up proteomics data and further by changes in corresponding biosynthetic pathways under infection-like conditions and during actual infection of host cells. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling...
Amyloid is an important class of proteinaceous material because of its close association with protein misfolding disorders such as Alzheimer’s disease and type II diabetes. Although the degree of stiffness of amyloid is critical to the understanding of its pathological and biological functions, current estimates of the rigidity of these β-sheet–rich protein aggregates range from soft (108 Pa) to hard (1010 Pa) depending on the method used. Here, we use time-resolved 4D EM to directly and noninvasively measure the oscillatory dynamics of freestanding, self-supporting amyloid beams and their rigidity. The dynamics of a single structure, not an ensemble, were visualized in space and time by imaging in the microscope an amyloid–dye cocrystal that, upon excitation, converts light into mechanical work. From the oscillatory motion, together with tomographic reconstructions of three studied amyloid beams, we determined the Young modulus of these highly ordered, hydrogen-bonded β-sheet structures. We find that amyloid materials are very stiff (109 Pa). The potential biological relevance of the deposition of such a highly rigid biomaterial in vivo are discussed.
Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffin-embedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity...
Gu, Hong; Zhang, Shuming; Wong, Kin-Yiu; Radak, Brian K.; Dissanayake, Thakshila; Kellerman, Daniel L.; Dai, Qing; Miyagi, Masaru; Anderson, Vernon E.; York, Darrin M.; Piccirilli, Joseph A.; Harris, Michael E.
Fonte: National Academy of SciencesPublicador: National Academy of Sciences
Enzymes function by stabilizing reaction transition states; therefore, comparison of the transition states of enzymatic and nonenzymatic model reactions can provide insight into biological catalysis. Catalysis of RNA 2′-O-transphosphorylation by ribonuclease A is proposed to involve electrostatic stabilization and acid/base catalysis, although the structure of the rate-limiting transition state is uncertain. Here, we describe coordinated kinetic isotope effect (KIE) analyses, molecular dynamics simulations, and quantum mechanical calculations to model the transition state and mechanism of RNase A. Comparison of the 18O KIEs on the 2′O nucleophile, 5′O leaving group, and nonbridging phosphoryl oxygens for RNase A to values observed for hydronium- or hydroxide-catalyzed reactions indicate a late anionic transition state. Molecular dynamics simulations using an anionic phosphorane transition state mimic suggest that H-bonding by protonated His12 and Lys41 stabilizes the transition state by neutralizing the negative charge on the nonbridging phosphoryl oxygens. Quantum mechanical calculations consistent with the experimental KIEs indicate that expulsion of the 5′O remains an integral feature of the rate-limiting step both on and off the enzyme. Electrostatic interactions with positively charged amino acid site chains (His12/Lys41)...
MicroRNAs (miRNAs) are small 19- to 24-nt noncoding RNAs that have the capacity to regulate fundamental biological processes essential for cancer initiation and progression. In cancer, miRNAs may function as oncogenes or tumor suppressors. Here, we conducted global profiling for miRNAs in a cohort of stage 1 nonsmall cell lung cancers (n = 81) and determined that miR-486 was the most down-regulated miRNA in tumors compared with adjacent uninvolved lung tissues, suggesting that miR-486 loss may be important in lung cancer development. We report that miR-486 directly targets components of insulin growth factor (IGF) signaling including insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and phosphoinositide-3-kinase, regulatory subunit 1 (alpha) (PIK3R1, or p85a) and functions as a potent tumor suppressor of lung cancer both in vitro and in vivo. Our findings support the role for miR-486 loss in lung cancer and suggest a potential biological link to p53.
Physical and biological systems are often involved with coupled processes of different time scales. In the system with electronic and atomic motions, for example, the interplay between the atomic motion along the same energy landscape and the electronic hopping between different landscapes is critical: the system behavior largely depends on whether the intralandscape motion is slower (adiabatic) or faster (nonadiabatic) than the interlandscape hopping. For general nonequilibrium dynamics where Hamiltonian or energy function is unknown a priori, the challenge is how to extend the concepts of the intra- and interlandscape dynamics. In this paper we establish a theoretical framework for describing global nonequilibrium and nonadiabatic complex system dynamics by transforming the coupled landscapes into a single landscape but with additional dimensions. On this single landscape, dynamics is driven by gradient of the potential landscape, which is closely related to the steady-state probability distribution of the enlarged dimensions, and the probability flux, which has a curl nature. Through an example of a self-regulating gene circuit, we show that the curl flux has dramatic effects on gene regulatory dynamics. The curl flux and landscape framework developed here are easy to visualize and can be used to guide further investigation of physical and biological nonequilibrium systems.
Many biases affect scientific research, causing a waste of resources, posing a threat to human health, and hampering scientific progress. These problems are hypothesized to be worsened by lack of consensus on theories and methods, by selective publication processes, and by career systems too heavily oriented toward productivity, such as those adopted in the United States (US). Here, we extracted 1,174 primary outcomes appearing in 82 meta-analyses published in health-related biological and behavioral research sampled from the Web of Science categories Genetics & Heredity and Psychiatry and measured how individual results deviated from the overall summary effect size within their respective meta-analysis. We found that primary studies whose outcome included behavioral parameters were generally more likely to report extreme effects, and those with a corresponding author based in the US were more likely to deviate in the direction predicted by their experimental hypotheses, particularly when their outcome did not include additional biological parameters. Nonbehavioral studies showed no such “US effect” and were subject mainly to sampling variance and small-study effects, which were stronger for non-US countries. Although this latter finding could be interpreted as a publication bias against non-US authors...
We provide an experimental demonstration that young infants possess abstract biological expectations about animals. Our findings represent a major breakthrough in the study of the foundations of human knowledge. In four experiments, 8-mo-old infants expected novel objects they categorized as animals to have filled insides. Thus, infants detected a violation when objects that were self-propelled and agentive were revealed to be hollow, or when an object that was self-propelled and furry rattled when shaken, as though mostly hollow. We describe possible characterizations of infants’ expectations about animals’ insides, including a characterization that emphasizes human predator–prey adaptations. We also discuss how infants’ expectation that animals have insides lays a foundation for the development of more advanced biological knowledge.
A conversion between macromolecular shapes—a conformational change—is usually the mechanism that gives function to biological macromolecules. Single-molecule force spectroscopy probes conformational changes by applying force to individual macromolecules and recording their response, or “mechanical fingerprints”, in the form of force–extension curves. The mechanical fingerprints of proteins, nucleic acids, and their assemblies often feature elaborate signatures that reflect the complexity of the underlying biomolecular interactions. This study introduces a transformation that converts—in a model-free way—the mechanical fingerprints of a complex system into a map of force-dependent transition rates. Once transformed into a rate map, the mechanical fingerprints can be interpreted in terms of the activation barriers and the intrinsic timescales of a biological process.
Acute myeloid leukemia (AML) consists of a group of hematopoietic malignancies with considerable diversities in clinical and biological features. Recently, not only genetic abnormalities but also “oncometabolites,” such as 2-hydroxyglutarate (2-HG), have been found to play a role in driving AML pathogenesis and serve as potential disease markers. In this study on a large cohort of AML, we found that the serum 2-HG level was increased in 62 of 367 (17%) cases with distinct hematologic and biological features. Survival analysis performed in 234 patients without prognostic cytogenetic markers showed that increased 2-HG level was a poor predictor, demonstrating the potential of serum 2-HG as an independent marker for outcome evaluation of AML.
Glahn, David C.; Kent, Jack W.; Sprooten, Emma; Diego, Vincent P.; Winkler, Anderson M.; Curran, Joanne E.; McKay, D. Reese; Knowles, Emma E.; Carless, Melanie A; Göring, Harald H. H.; Dyer, Thomas D.; Olvera, Rene L.; Fox, Peter T.; Almasy, Laura; Charl
Fonte: National Academy of SciencesPublicador: National Academy of Sciences
Identification of genes associated with brain aging should improve our understanding of the biological processes that govern normal age-related decline. In randomly selected pedigrees, we documented profound aging effects from young adulthood to old age (18–83 years) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for shared genetic determination was observed. Applying a gene-by-environment interaction analysis where age is an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration with age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. Identifying brain-aging traits is a critical first step in delineating the biological mechanisms of successful aging.
The cell cytoplasm contains a complex array of macromolecules at concentrations exceeding 300 g/L. The natural, most relevant state of a biological macromolecule is thus a “crowded” one. Moving quantitative protein chemistry from dilute solution to the inside of living cells represents a major frontier that will affect not only our fundamental biological knowledge, but also efforts to produce and stabilize protein-based pharmaceuticals. We show that the bacterial cytosol actually destabilizes our test protein, contradicting most theoretical predictions, but in agreement with a novel Escherichia coli model.
We report the first to our knowledge genetically engineered honeybees, which are important pollinators and interesting biological models for the study of social and complex behaviors as well as caste and sexual development. This genetic manipulation tool will enable systematic studies of biological processes in an organism building complex societies. We demonstrate highly efficient integration and expression of piggyBac-derived cassettes in the honeybee that make this system applicable to colony-based screening approaches and useful for an average beekeeping facility. This cassette was stably and efficiently transmitted and expressed in progeny by two different promoters, offering the prospect for activation or inhibition of gene functions under conditions of stage- and tissue-specific promoters.
Many complex biological phenotypes are multifactorial in nature, yet current strategies for studying biological systems are limited by the inability to generate and track complex combinatorial cellular perturbations in a scalable fashion. Here, we introduce a method, Combinatorial Genetics En Masse (CombiGEM), that allows both facile generation of high-order combinations and high-throughput characterization of pooled populations using next-generation sequencing. We apply CombiGEM to identify genetic combinations that enhance killing of highly antibiotic-resistant bacteria with antibiotics, thus providing potential targets for antimicrobial development. We envision that CombiGEM will be broadly useful for basic science and biotechnology applications, such as complex genetic screening, identification of novel drug targets, interactome mapping, and synthetic circuit characterization.
Because of their promotional effects on plant growth and development, rare earth elements (REEs) have been widely used in agriculture as plant growth stimulants. However, little is known about the cellular basis of REE actions in plants, and the biological safety of farm REE application in agriculture has not yet attracted enough attention. Here, we show that two types of REEs entered plant cells by endocytosis, and that they both had an activating effect on endocytosis. Moreover, we found that a portion of REEs was finally deposited in plant cells. Our data thus provide novel insights into the cellular mechanisms of REE actions in plants, and may also serve as valuable documentation for evaluating the biological safety of REE application in agriculture.