scholarly journals The analysis of the polyamine oxidase genes in the methylotrophic yeast Komagataella phaffii

2019 ◽  
Vol 17 (4) ◽  
pp. 47-55
Author(s):  
Alina V. Ivanova ◽  
Anton V. Sidorin ◽  
Elena V. Sambuk ◽  
Andrei M. Rumyantsev
Keyword(s):  
Pantothenic Acid ◽  
Methylotrophic Yeast ◽  
Living Cells ◽  
Polyamine Oxidase ◽  
Biological Processes ◽  
Komagataella Phaffii ◽  
Copy Numbers ◽  
Wide Range ◽  
Pichia Pastoris Yeast ◽  
Gene Orthologs

Polyamines are present in all living cells and regulate a wide range of biological processes. In Saccharomyces cerevisiae the polyamine oxidase Fms1p converts spermine to spermidine and 3-aminopropionaldehyde, which is necessary for the synthesis of pantothenic acid and hypusination. This paper shows that S. cerevisiae FMS1 gene orthologs are present in all major representatives of the Saccharomycotina subdivision, but their copy numbers are different. In the Komagataella phaffii (Pichia pastoris) yeast, two polyamine oxidase genes (KpFMS1 and KpFMS2) were identified, and the regulation of their promoters activity was studied.

scholarly journals Quantitative linear dichroism imaging of molecular processes in living cells made simple by open software tools

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Alexey Bondar ◽  
Olga Rybakova ◽  
Josef Melcr ◽  
Jan Dohnálek ◽  
Petro Khoroshyy ◽  
...  
Keyword(s):  
Biological Systems ◽  
Linear Dichroism ◽  
Quantitative Information ◽  
Living Cells ◽  
Software Tools ◽  
Model Systems ◽  
Membrane Properties ◽  
Polarization Microscopy ◽  
Molecular Processes ◽  
Wide Range

AbstractFluorescence-detected linear dichroism microscopy allows observing various molecular processes in living cells, as well as obtaining quantitative information on orientation of fluorescent molecules associated with cellular features. Such information can provide insights into protein structure, aid in development of genetically encoded probes, and allow determinations of lipid membrane properties. However, quantitating and interpreting linear dichroism in biological systems has been laborious and unreliable. Here we present a set of open source ImageJ-based software tools that allow fast and easy linear dichroism visualization and quantitation, as well as extraction of quantitative information on molecular orientations, even in living systems. The tools were tested on model synthetic lipid vesicles and applied to a variety of biological systems, including observations of conformational changes during G-protein signaling in living cells, using fluorescent proteins. Our results show that our tools and model systems are applicable to a wide range of molecules and polarization-resolved microscopy techniques, and represent a significant step towards making polarization microscopy a mainstream tool of biological imaging.

scholarly journals Energetics of mesoscale cell turbulence in two-dimensional monolayers

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Shao-Zhen Lin ◽  
Wu-Yang Zhang ◽  
Dapeng Bi ◽  
Bo Li ◽  
Xi-Qiao Feng
Keyword(s):  
Kinetic Energy ◽  
Tumor Metastasis ◽  
Cell Types ◽  
Boltzmann Distribution ◽  
Scaling Exponent ◽  
Biological Processes ◽  
Two Dimensional ◽  
Cell Monolayers ◽  
Wide Range ◽  
Epithelial Cell Monolayers

AbstractInvestigation of energy mechanisms at the collective cell scale is a challenge for understanding various biological processes, such as embryonic development and tumor metastasis. Here we investigate the energetics of self-sustained mesoscale turbulence in confluent two-dimensional (2D) cell monolayers. We find that the kinetic energy and enstrophy of collective cell flows in both epithelial and non-epithelial cell monolayers collapse to a family of probability density functions, which follow the q-Gaussian distribution rather than the Maxwell–Boltzmann distribution. The enstrophy scales linearly with the kinetic energy as the monolayer matures. The energy spectra exhibit a power-decaying law at large wavenumbers, with a scaling exponent markedly different from that in the classical 2D Kolmogorov–Kraichnan turbulence. These energetic features are demonstrated to be common for all cell types on various substrates with a wide range of stiffness. This study provides unique clues to understand active natures of cell population and tissues.

scholarly journals Reversing resistance: different routes and common themes across pathogens

2017 ◽  
Vol 284 (1863) ◽  
pp. 20171619 ◽  
Author(s):  
Richard C. Allen ◽  
Jan Engelstädter ◽  
Sebastian Bonhoeffer ◽  
Bruce A. McDonald ◽  
Alex R. Hall
Keyword(s):  
Fitness Cost ◽  
Biological Processes ◽  
Short Supply ◽  
Compensatory Evolution ◽  
Wide Range ◽  
Different Types ◽  
Cost Of Resistance

Resistance spreads rapidly in pathogen or pest populations exposed to biocides, such as fungicides and antibiotics, and in many cases new biocides are in short supply. How can resistance be reversed in order to prolong the effectiveness of available treatments? Some key parameters affecting reversion of resistance are well known, such as the fitness cost of resistance. However, the population biological processes that actually cause resistance to persist or decline remain poorly characterized, and consequently our ability to manage reversion of resistance is limited. Where do susceptible genotypes that replace resistant lineages come from? What is the epidemiological scale of reversion? What information do we need to predict the mechanisms or likelihood of reversion? Here, we define some of the population biological processes that can drive reversion, using examples from a wide range of taxa and biocides. These processes differ primarily in the origin of revertant genotypes, but also in their sensitivity to factors such as coselection and compensatory evolution that can alter the rate of reversion, and the likelihood that resistance will re-emerge upon re-exposure to biocides. We therefore argue that discriminating among different types of reversion allows for better prediction of where resistance is most likely to persist.

scholarly journals The RhoA-ROCK pathway in the regulation of T and B cell responses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2295 ◽  
Author(s):  
Edd Ricker ◽  
Luvana Chowdhury ◽  
Woelsung Yi ◽  
Alessandra B. Pernis
Keyword(s):  
Immune Responses ◽  
Biological Processes ◽  
Dynamic Interactions ◽  
Cell Responses ◽  
Important Mediator ◽  
Downstream Effectors ◽  
Wide Range ◽  
Response To Stress ◽  
The Impact ◽  
Rho Kinases

Effective immune responses require the precise regulation of dynamic interactions between hematopoietic and non-hematopoietic cells. The Rho subfamily of GTPases, which includes RhoA, is rapidly activated downstream of a diverse array of biochemical and biomechanical signals, and is emerging as an important mediator of this cross-talk. Key downstream effectors of RhoA are the Rho kinases, or ROCKs. The ROCKs are two serine-threonine kinases that can act as global coordinators of a tissue’s response to stress and injury because of their ability to regulate a wide range of biological processes. Although the RhoA-ROCK pathway has been extensively investigated in the non-hematopoietic compartment, its role in the immune system is just now becoming appreciated. In this commentary, we provide a brief overview of recent findings that highlight the contribution of this pathway to lymphocyte development and activation, and the impact that dysregulation in the activation of RhoA and/or the ROCKs may exert on a growing list of autoimmune and lymphoproliferative disorders.

scholarly journals Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

2021 ◽  
Vol 17 (2) ◽  
pp. e1008767
Author(s):  
Zutan Li ◽  
Hangjin Jiang ◽  
Lingpeng Kong ◽  
Yuanyuan Chen ◽  
Kun Lang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prediction Accuracy ◽  
Cross Validation ◽  
Biological Processes ◽  
Biological Functions ◽  
Learning Framework ◽  
Wide Range ◽  
Genomic Scale ◽  
Downstream Gene Expression ◽  
Fold Cross Validation

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

scholarly journals Dynamics in Copy Numbers of Five Plasmids of a DairyLactococcus lactisStrain under Dairy-Related Conditions Including Near-Zero Growth Rates

2018 ◽  
Vol 84 (11) ◽  
Author(s):  
Oscar van Mastrigt ◽  
Marcel M. A. N. Lommers ◽  
Yorick C. de Vries ◽  
Tjakko Abee ◽  
Eddy J. Smid
Keyword(s):  
Nutrient Limitation ◽  
Lactococcus Lactis ◽  
Growth Rates ◽  
Copy Number ◽  
Plasmid Copy ◽  
Content Type ◽  
Copy Numbers ◽  
Wide Range ◽  
Zero Growth ◽  
The Impact

ABSTRACTLactic acid bacteria can carry multiple plasmids affecting their performance in dairy fermentations. The expression of plasmid-borne genes and the activity of the corresponding proteins are severely affected by changes in the numbers of plasmid copies. We studied the impact of growth rate on the dynamics of plasmid copy numbers at high growth rates in chemostat cultures and down to near-zero growth rates in retentostat cultures. Five plasmids of the dairy strainLactococcus lactisFM03-V1 were selected, and these varied in size (3 to 39 kb), in replication mechanism (theta or rolling circle), and in putative (dairy-associated) functions. The copy numbers ranged from 1.5 to 40.5, and the copy number of theta-type replicating plasmids was negatively correlated to the plasmid size. Despite the extremely wide range of growth rates (0.0003 h−1to 0.6 h−1), the copy numbers of the five plasmids were stable and only slightly increased at near-zero growth rates, showing that the plasmid replication rate was strictly controlled. One low-copy-number plasmid, carrying a large exopolysaccharide gene cluster, was segregationally unstable during retentostat cultivations, reflected in a complete loss of the plasmid in one of the retentostat cultures. The copy number of the five plasmids was also hardly affected by varying the pH value, nutrient limitation, or the presence of citrate (maximum 2.2-fold), signifying the stability in copy number of the plasmids.IMPORTANCELactococcus lactisis extensively used in starter cultures for dairy fermentations. Important traits for the growth and survival ofL. lactisin dairy fermentations are encoded by genes located on plasmids, such as genes involved in lactose and citrate metabolism, protein degradation, oligopeptide uptake, and bacteriophage resistance. Because the number of plasmid copies could affect the expression of plasmid-borne genes, it is important to know the factors that influence the plasmid copy numbers. We monitored the plasmid copy numbers ofL. lactisat near-zero growth rates, characteristic for cheese ripening. Moreover, we analyzed the effects of pH, nutrient limitation, and the presence of citrate. This showed that the plasmid copy numbers were stable, giving insight into plasmid copy number dynamics in dairy fermentations.

scholarly journals SANTA-SIM: simulating viral sequence evolution dynamics under selection and recombination

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Abbas Jariani ◽  
Christopher Warth ◽  
Koen Deforche ◽  
Pieter Libin ◽  
Alexei J Drummond ◽  
...  
Keyword(s):  
Software Package ◽  
Point Mutations ◽  
Sequence Evolution ◽  
Biological Processes ◽  
Viral Sequence ◽  
Recombination Point ◽  
Wide Range ◽  
Cross Platform ◽  
Evolution Dynamics ◽  
Inference Methods

Abstract Simulations are widely used to provide expectations and predictive distributions under known conditions against which to compare empirical data. Such simulations are also invaluable for testing and comparing the behaviour and power of inference methods. We describe SANTA-SIM, a software package to simulate the evolution of a population of gene sequences forwards through time. It models the underlying biological processes as discrete components: replication, recombination, point mutations, insertion–deletions, and selection under various fitness models and population size dynamics. The software is designed to be intuitive to work with for a wide range of users and executable in a cross-platform manner.

Raman Imaging of Small Biomolecules

2019 ◽  
Vol 48 (1) ◽  
pp. 347-369 ◽  
Author(s):  
Yihui Shen ◽  
Fanghao Hu ◽  
Wei Min
Keyword(s):  
Imaging Techniques ◽  
Living Cells ◽  
Raman Imaging ◽  
Biological Processes ◽  
Comprehensive Knowledge ◽  
Contrast Mechanisms ◽  
Recent Developments ◽  
Imaging Methodology ◽  
Small Biomolecules ◽  
Microscopic Techniques

Imaging techniques greatly facilitate the comprehensive knowledge of biological systems. Although imaging methodology for biomacromolecules such as protein and nucleic acids has been long established, microscopic techniques and contrast mechanisms are relatively limited for small biomolecules, which are equally important participants in biological processes. Recent developments in Raman imaging, including both microscopy and tailored vibrational tags, have created exciting opportunities for noninvasive imaging of small biomolecules in living cells, tissues, and organisms. Here, we summarize the principle and workflow of small-biomolecule imaging by Raman microscopy. Then, we review recent efforts in imaging, for example, lipids, metabolites, and drugs. The unique advantage of Raman imaging has been manifested in a variety of applications that have provided novel biological insights.

scholarly journals GeneFishing to reconstruct context specific portraits of biological processes

2019 ◽  
Vol 116 (38) ◽  
pp. 18943-18950 ◽  
Author(s):  
Ke Liu ◽  
Elizabeth Theusch ◽  
Yun Zhou ◽  
Tal Ashuach ◽  
Andrea C. Dose ◽  
...  
Keyword(s):  
Cholesterol Metabolism ◽  
Hepatoma Cell ◽  
Biological Processes ◽  
Human Hepatoma Cell ◽  
Hepatoma Cell Lines ◽  
Genomic Technologies ◽  
Rnaseq Data ◽  
Wide Range ◽  
Context Specific ◽  
Diverse Data

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene–gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as “bait” to “fish out” (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I (GLO1) as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that GLO1 knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for GLO1 in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications.

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