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.
A major advance of the last 20 y at the interface of biological, environmental, and conservation sciences has been the demonstration that plant biodiversity positively influences ecosystem function. Linking these results to applied conservation efforts hinges on the assumption that biodiversity is actually declining at the local scale at which diversity–function relationships are strongest. Our compilation and analysis of a global database of >16,000 repeat survey vegetation plots from habitats across the globe directly contradict this assumption. We find no general tendency for local-scale plant species diversity to decline over the last century, calling into question the widespread use of ecosystem function experiments to argue for the importance of biodiversity conservation in nature.
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.
Human mucosal surfaces contain a wide range of microorganisms. The biological effects of these organisms are largely unknown. Large-scale metagenomic sequencing is emerging as a method to identify novel microbes. Unexpectedly, we identified DNA sequences homologous to virus ATCV-1, an algal virus not previously known to infect humans, in oropharyngeal samples obtained from healthy adults. The presence of ATCV-1 was associated with a modest but measurable decrease in cognitive functioning. A relationship between ATCV-1 and cognitive functioning was confirmed in a mouse model, which also indicated that exposure to ATCV-1 resulted in changes in gene expression within the brain. Our study indicates that viruses in the environment not thought to infect humans can have biological effects.
The solvent in biological reactions plays an active role in protein function; however, correlating solvation dynamics with specific biological scenarios remains a scientific challenge. Here, we followed time-dependent changes in solvation dynamics using terahertz absorption spectroscopy during proteolysis of collagen substrates by a metalloproteinase. Unexpectedly, we revealed that solvation dynamics do not follow the traditional enzymatic steady-state kinetic theory but generate long-lasting protein–water-coupled motions that last longer than a single catalytic cycle and are substrate-specific. These prolonged solvation dynamics contribute to the net enzyme reactivity impacting substrate binding, positional catalysis, and product release.
Forecasting reservoirs of zoonotic disease is a pressing public health priority. We apply machine learning to datasets describing the biological, ecological, and life history traits of rodents, which collectively carry a disproportionate number of zoonotic pathogens. We identify particular rodent species predicted to be novel zoonotic reservoirs and geographic regions from which new emerging pathogens are most likely to arise. We also describe trait profiles—complexes of biological features—that distinguish reservoirs from nonreservoirs. Generally, the most permissive rodent reservoirs display a fast-paced life history strategy, maximizing near-term fitness by having many altricial young that begin reproduction early and reproduce frequently. These findings may constitute an important lead in guiding the search for novel disease reservoirs in the wild.
Prostate cancer has an unpredictable natural history: While most tumors are clinically indolent, some patients display lethal phenotypes. Serum prostate-specific antigen is the most often used test in prostate cancer but screening is controversial. Treatment options are limited for metastatic disease, hence the need for early diagnosis. Prostate cancer antigen 3 (PCA3), a long noncoding RNA, is the most specific biomarker identified and approved as a diagnostic test. However, its inherent biological function (if any) has remained elusive. We uncovered a negative transdominant oncogenic role for PCA3 that down-regulates an unrecognized tumor suppressor gene, PRUNE2 (a human homolog of the Drosophila prune gene) thereby promoting malignant cell growth. This work defines a unique biological function for PCA3 in prostate cancer.