Biological Features
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2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Hong Ding ◽  
Juan Xu ◽  
Zhimei Lin ◽  
Jingcao Huang ◽  
Fangfang Wang ◽  
...  

AbstractMultiple myeloma (MM) is a treatable plasma cell cancer with no cure. Clinical evidence shows that the status of minimal residual disease (MRD) after treatment is an independent prognostic factor of MM. MRD indicates the depth of post-therapeutic remission. In this review article, we outlined the major clinical trials that have determined the prognostic value of MRD in MM. We also reviewed different methods that were used for MM MRD assessment. Most important, we reviewed our current understanding of MM MRD biology. MRD studies strongly indicate that MRD is not a uniform declination of whole MM tumor population. Rather, MM MRD exhibits unique signatures of cytogenetic aberration and gene expression profiles, unlike those of MM cells before therapy. Diagnostic high-risk MM and low-risk MM exhibited a diversity of MRD features. Clonal evaluation may occur at the MRD stage in MM. The dynamics from the diagnostic MM to MRD correlate with the disease prognosis. Lastly, on the aspect of omics, we performed data-based analysis to address the biological features underlying the course of diagnostic-to-MRD MM. To summarize, the MRD stage of disease represents a critical step in MM pathogenesis and progression. Demonstration of MM MRD biology should help us to deal with the curative difficulties.


Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3604
Author(s):  
Lila S. Nolan ◽  
Angela N. Lewis ◽  
Qingqing Gong ◽  
James J. Sollome ◽  
Olivia N. DeWitt ◽  
...  

The application of metabolomics in neonatology offers an approach to investigate the complex relationship between nutrition and infant health. Characterization of the metabolome of human milk enables an investigation into nutrients that affect the neonatal metabolism and identification of dietary interventions for infants at risk of diseases such as necrotizing enterocolitis (NEC). In this study, we aimed to identify differences in the metabolome of breast milk of 48 mothers with preterm infants with NEC and non-NEC healthy controls. A minimum significant difference was observed in the human milk metabolome between the mothers of infants with NEC and mothers of healthy control infants. However, significant differences in the metabolome related to fatty acid metabolism, oligosaccharides, amino sugars, amino acids, vitamins and oxidative stress-related metabolites were observed when comparing milk from mothers with control infants of ≤1.0 kg birth weight and >1.5 kg birth weight. Understanding the functional biological features of mothers’ milk that may modulate infant health is important in the future of tailored nutrition and care of the preterm newborn.


2021 ◽  
Author(s):  
Abdulbasit Haliru Yakubu ◽  
Muhammad Mustapha Muhammad

Multi-Drug Resistant (MDR) Staphylococcus aureus is an important bacteria with clinical and economic implications. Plants including Garcinia kola provides bioactive principles with diverse structural and biological features. Tyrosyl-tRNA synthetase (TyrRS) is targeted in antibacterial drug discovery as its implicated in bacterial protein synthesis. The n-Butanol fraction of Garcinia kola root extract recorded the highest activity against MDR staph aureus (18.50±0.41) compared to the chloroform (10.00±2.12) and methanol (8.16±0.62) extract, with no activity recorded with the n-Hexane extract. Analysis of the n-Butanol fraction on GC-MS recorded 14 phytoconstituents with varying structural composition; containing important scaffolds & motifs of benzoquinone, imidazole[1,2-a]pyridine, chlorocarbazole and azetidine that present key pharmaceuticals as antibiotic and for drug development. Further insilico molecular docking studies of these compounds on antibacterial drug target; Tyrosyl-tRNA synthetase (PDB 1JIJ) from MDR staph aureus were documented. Nine (9) compounds had good binding scores ranging from -4.63 to -7.08 kcal/mol; with CID_590350 having the highest score. The compounds formed various bonding with the 1JIJ amino acid residues including H-bond, van der waal and π interactions. Five (5) compounds; CID_619583 (9,9-Dichloro-9-silafluorene), CID_5732 (Zolpidem), CID_616643 (Pyridazine-3,5-dicarbonitrile, 1,6-dihydro-4-amino-6-imino-1-(2-nitrophenyl)), CID_16486 ((S)-(-)-2-Azetidinecarboxlic acid) and CID_66747 (2-Hydroxyethyl benzoate) showed favorable ADME properties, while their MD stimulation analysis revealed stable binding capabilities with the drug target. CID_16486 and CID_66747 bind to the most active binding pocket (Drug score: 0.82 and 0.72) while CID_619583 tends to bind outside the active binding pocket. Therefore, these compounds from the root of Garcinia kola are considered as suitable prospective bioactive compounds against MDR Staphylococcus aureus after successful in vitro and in silico experimental validation.


2021 ◽  
Author(s):  
Naoto Tanaka ◽  
Yuko Mogi ◽  
Takayuki Fujiwara ◽  
Kannosuke Yabe ◽  
Yukiho Toyama ◽  
...  

The unicellular alga Cyanidioschyzon merolae has a simple cellular structure: each cell has one nucleus, one mitochondrion, one chloroplast, and one peroxisome. This simplicity offers unique advantages for investigating organellar proliferation and the cell cycle. Here, we describe CZON-cutter, an engineered clustered, regularly interspaced, short palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9) system for simultaneous genome editing and organellar visualization. We engineered a C. merolae strain expressing a nuclear-localized Cas9-Venus nuclease for targeted editing of any locus defined by a single guide RNA (sgRNA). We then successfully edited the algal genome and visualized the mitochondrion and peroxisome in transformants using fluorescent protein reporters with different excitation wavelengths. Fluorescent protein labeling of organelles in living transformants allows us to validate phenotypes associated with organellar proliferation and the cell cycle, even when the edited gene is essential. Combined with the exceptional biological features of C. merolae, CZON-cutter will be instrumental for investigating cellular and organellar division in a high-throughput manner.


Cells ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2692
Author(s):  
Eric Röttinger

The capacity to regenerate lost or injured body parts is a widespread feature within metazoans and has intrigued scientists for centuries. One of the most extreme types of regeneration is the so-called whole body regenerative capacity, which enables regeneration of fully functional organisms from isolated body parts. While not exclusive to this habitat, whole body regeneration is widespread in aquatic/marine invertebrates. Over the past decade, new whole-body research models have emerged that complement the historical models Hydra and planarians. Among these, the sea anemone Nematostella vectensis has attracted increasing interest in regard to deciphering the cellular and molecular mechanisms underlying the whole-body regeneration process. This manuscript will present an overview of the biological features of this anthozoan cnidarian as well as the available tools and resources that have been developed by the scientific community studying Nematostella. I will further review our current understanding of the cellular and molecular mechanisms underlying whole-body regeneration in this marine organism, with emphasis on how comparing embryonic development and regeneration in the same organism provides insight into regeneration specific elements.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 339-339
Author(s):  
Mariya Miroshnikova ◽  
Elena Miroshnikova ◽  
Alexey Sizentsov ◽  
Azamat Arinzhanov ◽  
Yuliya Kilyakova

Abstract One of the most promising ways to improve the effectiveness of fish farming is the use of phytobiotics in the diet of fish. On this basis, we set the aim to evaluate the effectiveness of the Quercus cortex extract in the concentration of 1 mg/kg on biological features and the productivity of carp. The object of the research was yearling carp grown in the conditions of Orenburgskiy Osetr LLC. Two groups (n = 20) were formed by the method of analogs to conduct the research. After the adaption period (7 days), the groups came to the experimental period (35 days). The feed KRK-110–1 produced by PJSC Orenburg Combined-Feed Plant was used as the basal diet. The live fish were monitored weekly by individual weighing during the accounting period. The elemental composition was determined by the method of atomic emission and mass spectrometry (ICP-AES and ICP-MS). The microflora analysis was carried out by the method of metagenomic sequencing. The use of the Quercus cortex extract in the diet in the studied concentration increased body weight by 15.1% (P ≤ 0.05) compared to the control group. There was experimentally revealed a stimulating effect on the population growth of individual representatives of the microbiome (Luteolibacter, Lactococcus) (P ≤ 0.05) without significantly changing the overall picture of the microbial profile, which, in our view, affects the metabolic processes, in particular, by stimulating the formation of biologically available forms of essential elements and their subsequent accumulation in the tissues of the studied fish. Thus, the experimental group found: (against the background of an increase in the total mineralization (ash residue) by 17.95 % (P ≤ 0.05)) the calcium content increased by 133.9% (P ≤ 0.05), phosphorus by 83% (P ≤ 0.05), iron by 337.7% (P ≤ 0.05), respectively, in comparison with the control group.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Liqian Zhou ◽  
Zhao Wang ◽  
Xiongfei Tian ◽  
Lihong Peng

Abstract Background Long noncoding RNAs (lncRNAs) play important roles in various biological and pathological processes. Discovery of lncRNA–protein interactions (LPIs) contributes to understand the biological functions and mechanisms of lncRNAs. Although wet experiments find a few interactions between lncRNAs and proteins, experimental techniques are costly and time-consuming. Therefore, computational methods are increasingly exploited to uncover the possible associations. However, existing computational methods have several limitations. First, majority of them were measured based on one simple dataset, which may result in the prediction bias. Second, few of them are applied to identify relevant data for new lncRNAs (or proteins). Finally, they failed to utilize diverse biological information of lncRNAs and proteins. Results Under the feed-forward deep architecture based on gradient boosting decision trees (LPI-deepGBDT), this work focuses on classify unobserved LPIs. First, three human LPI datasets and two plant LPI datasets are arranged. Second, the biological features of lncRNAs and proteins are extracted by Pyfeat and BioProt, respectively. Thirdly, the features are dimensionally reduced and concatenated as a vector to represent an lncRNA–protein pair. Finally, a deep architecture composed of forward mappings and inverse mappings is developed to predict underlying linkages between lncRNAs and proteins. LPI-deepGBDT is compared with five classical LPI prediction models (LPI-BLS, LPI-CatBoost, PLIPCOM, LPI-SKF, and LPI-HNM) under three cross validations on lncRNAs, proteins, lncRNA–protein pairs, respectively. It obtains the best average AUC and AUPR values under the majority of situations, significantly outperforming other five LPI identification methods. That is, AUCs computed by LPI-deepGBDT are 0.8321, 0.6815, and 0.9073, respectively and AUPRs are 0.8095, 0.6771, and 0.8849, respectively. The results demonstrate the powerful classification ability of LPI-deepGBDT. Case study analyses show that there may be interactions between GAS5 and Q15717, RAB30-AS1 and O00425, and LINC-01572 and P35637. Conclusions Integrating ensemble learning and hierarchical distributed representations and building a multiple-layered deep architecture, this work improves LPI prediction performance as well as effectively probes interaction data for new lncRNAs/proteins.


2021 ◽  
Author(s):  
Jingqi Zhou ◽  
Ake Liu ◽  
Funan He ◽  
Yunbin Zhang ◽  
Libing Shen ◽  
...  

AbstractThe white-blotched river stingray (Potamotrygon leopoldi) is a cartilaginous fish native to the Xingu River, a tributary of the Amazon River system. It possesses a lot of unique biological features such as disc-like body shape, bizarre color pattern and living in freshwater habitat while most stingrays and their close relatives are sea dwellers. As a member of the Potamotrygonidae family, P. leopoldi bears evolutionary signification in fish phylogeny, niche adaptation and skeleton formation. In this study, we present its draft genome of 4.11 Gb comprised of 16,227 contigs and 13,238 scaffolds, which has contig N50 of 3,937 kilobases and scaffold N50 of 5,675 kilobases in size. Our analysis shows that P. leopoldi is a slow-evolving fish, diverged from elephant shark about 96 million years ago. We find that two gene families related to immune system, immunoglobulin heavy constant delta genes, and T-cell receptor alpha/delta variable genes, stand out expanded in P. leopoldi only, suggesting robustness in response to freshwater pathogens in adapting novel environments. We also identified the Hox gene clusters in P. leopoldi and discovered that seven Hox genes shared by five representative fishes are missing in P. leopoldi. The RNA-seq data from P. leopoldi and other three fish species demonstrate that fishes have a more diversified tissue expression spectrum as compared to the corresponding mammalian data. Our functional studies suggest that the lack of genes encoding vitamin D-binding protein in cartilaginous (both P. leopoldi and Callorhinchus milii) fishes could partly explain the absence of hard bone in their endoskeleton. Overall, this genome resource provides new insights into the niche-adaptation, body plan and skeleton formation of P. leopoldi as well as the genome evolution in cartilaginous fish.


2021 ◽  
Author(s):  
Cedoljub Bundalovic-Torma ◽  
Darrell Desveaux ◽  
David S Guttman

A critical step in studying biological features (e.g., genetic variants, gene families, metabolic capabilities, or taxa) underlying traits or outcomes of interest is assessing their diversity and distribution. Accurate assessments of these patterns are essential for linking features to traits or outcomes and understanding their functional impact. Consequently, it is of crucial importance that the metrics employed for quantifying feature diversity can perform robustly under any evolutionary scenario. However, the standard metrics used for quantifying and comparing the distribution of features, such as prevalence, phylogenetic diversity, and related approaches, either do not take into consideration evolutionary history, or assume strictly vertical patterns of inheritance. Consequently, these approaches cannot accurately assess diversity for features that have undergone recombination or horizontal transfer. To address this issue, we have devised RecPD, a novel recombination-aware phylogenetic-diversity metric for measuring the distribution and diversity of features under all evolutionary scenarios. RecPD utilizes ancestral-state reconstruction to map the presence / absence of features onto ancestral nodes in a species tree, and then identifies potential recombination events in the evolutionary history of the feature. We also derive a number of related metrics from RecPD that can be used to assess and quantify evolutionary dynamics and correlation of feature evolutionary histories. We used simulation studies to show that RecPD reliably identifies evolutionary histories under diverse recombination and loss scenarios. We then apply RecPD in a real-world scenario in a preliminary study type III effector protein families secreted by the plant pathogenic bacterium Pseudomonas syringae and demonstrate that prevalence is an inadequate metric that obscures the potential impact of recombination. We believe RecPD will have broad utility for revealing and quantifying complex evolutionary processes for features at any biological level.


2021 ◽  
pp. 173-178
Author(s):  
S.V. Shevchenko ◽  
I.V. Mitrofanova

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