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BioTech, Volume 10, Issue 1 (March 2021) – 6 articles

Cover Story (view full-size image): Qiime2 is one of the most popular software tools used for analysis of output from metabarcoding experiments (e.g., sequencing of 16S, 18S, or ITS amplicons). Qiime2 introduced a novel and innovative data exchange format: the ‘Qiime2 artifact’. Qiime2 artifacts are structured compressed archives containing a dataset and its associated metadata. Examples of datasets are FASTQ reads, representative sequences in FASTA format, a phylogenetic tree in Newick format, while examples of metadata are the command that generated the artifact, information on the execution environment, citations on the used software, and all the metadata of the artifacts used to produce it. While artifacts can improve the shareability and reproducibility of Qiime2 workflows, they are less easily integrated with general bioinformatics pipelines. View this paper

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11 pages, 1282 KiB

Open AccessArticle

The Andalusian Registry of Donors for Biomedical Research: Five Years of History

by Rocío Aguilar-Quesada, Inés Aroca-Siendones, Leticia de la Torre, Sonia Panadero-Fajardo, Juan David Rejón, Ana María Sánchez-López and Blanca Miranda

BioTech 2021, 10(1), 6; https://doi.org/10.3390/biotech10010006 - 12 Mar 2021

Cited by 2 | Viewed by 3757

Abstract

The mission of the Andalusian Public Health System Biobank is to offer the best options for biological samples of human origin and associated clinical information, protecting the rights of citizens who donate their samples for research. Since the Andalusian Biobank provides high-quality biological samples of all types in a specified format, adapting the preanalytical phase according to the requirements of the research, prospective collection and distribution of samples are being prioritized in order to contribute to the sustainability of the Biobank. The Andalusian Registry of Donors for Biomedical Research is a tool for the recruitment of donors and the prospective collection of samples. Its operation is based on the informed consent of donors for their incorporation into the Registry and contact with possible donors under request from specific projects. An additional advantage of this unique initiative is to ensure that societal actors work together throughout the entire research process, establishing alliances with patient associations and groups to develop joint actions and promote biomedical research. Here, we describe the creation, ethical–legal aspects, management and results of the Andalusian Registry of Donors for Biomedical Research after five years of operation. Full article

(This article belongs to the Special Issue Recent Advances in Biobanking: New Perspectives from Laboratory to Regulation)

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6 pages, 750 KiB

Open AccessCommunication

Qiime Artifact eXtractor (qax): A Fast and Versatile Tool to Interact with Qiime2 Archives

by Andrea Telatin

BioTech 2021, 10(1), 5; https://doi.org/10.3390/biotech10010005 - 3 Mar 2021

Cited by 5 | Viewed by 4437

Abstract

Qiime2 is one of the most popular software tools used for analysis of output from metabarcoding experiments (e.g., sequencing of 16S, 18S, or ITS amplicons). Qiime2 introduced a novel and innovative data exchange format: the ‘Qiime2 artifact’. Qiime2 artifacts are structured compressed archives containing a dataset and its associated metadata. Examples of datasets are FASTQ reads, representative sequences in FASTA format, a phylogenetic tree in Newick format, while examples of metadata are the command that generated the artifact, information on the execution environment, citations on the used software, and all the metadata of the artifacts used to produce it. While artifacts can improve the shareability and reproducibility of Qiime2 workflows, they are less easily integrated with general bioinformatics pipelines. Accessing metadata in the artifacts also requires full Qiime2 installation. Qiime Artifact eXtractor (qax) allows users to easily interface with Qiime2 artifacts from the command line, without needing the full Qiime2 environment installed (or activated). Full article

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12 pages, 268 KiB

Open AccessCommentary

Oocyte Biobanks: Old Assumptions and New Challenges

by Pamela Tozzo

BioTech 2021, 10(1), 4; https://doi.org/10.3390/biotech10010004 - 18 Feb 2021

Cited by 4 | Viewed by 3330

Abstract

The preservation of fertility is a clinical issue that has been emerging considerably in recent decades, as the number of patients of childbearing age who risk becoming infertile for many reasons is increasing. The cryopreservation technique of oocytes has been developed for many years and nowadays constitutes a method of safe storage with impressive efficacy and high rates of successful thawing. The storage and use for research of oocytes taken for medical or non-medical can be carried out by both public and private structures, through egg sharing, voluntary egg donation and so-called “social freezing” for autologous use. This paper focuses on the oocyte bank as an emerging cryopreservation facility, in which a collaboration between public and private and the creation of a network of these biobanks can be useful in enhancing both their implementation and their functions. Good oocyte biobank practice would require that they be collected, stored, and used according to appropriate bioethical and bio-law criteria, collected and stored according to procedures that guarantee the best preservation of their structural components and a high level of safety, connected with appropriate procedures to protect the rights and privacy of the parties involved and associated with the results of the bio-molecular investigations that will be carried out gradually. Full article

(This article belongs to the Special Issue Recent Advances in Biobanking: New Perspectives from Laboratory to Regulation)

19 pages, 915 KiB

Open AccessArticle

Integrating Multi–Omics Data for Gene-Environment Interactions

by Yinhao Du, Kun Fan, Xi Lu and Cen Wu

BioTech 2021, 10(1), 3; https://doi.org/10.3390/biotech10010003 - 29 Jan 2021

Cited by 4 | Viewed by 4406

Abstract

Gene-environment (G×E) interaction is critical for understanding the genetic basis of complex disease beyond genetic and environment main effects. In addition to existing tools for interaction studies, penalized variable selection emerges as a promising alternative for dissecting G×E interactions. Despite the success, variable selection is limited in terms of accounting for multidimensional measurements. Published variable selection methods cannot accommodate structured sparsity in the framework of integrating multiomics data for disease outcomes. In this paper, we have developed a novel variable selection method in order to integrate multi-omics measurements in G×E interaction studies. Extensive studies have already revealed that analyzing omics data across multi-platforms is not only sensible biologically, but also resulting in improved identification and prediction performance. Our integrative model can efficiently pinpoint important regulators of gene expressions through sparse dimensionality reduction, and link the disease outcomes to multiple effects in the integrative G×E studies through accommodating a sparse bi-level structure. The simulation studies show the integrative model leads to better identification of G×E interactions and regulators than alternative methods. In two G×E lung cancer studies with high dimensional multi-omics data, the integrative model leads to an improved prediction and findings with important biological implications. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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1 pages, 170 KiB

Open AccessEditorial

Acknowledgment to Reviewers of BioTech in 2020

by BioTech Editorial Office

BioTech 2021, 10(1), 2; https://doi.org/10.3390/biotech10010002 - 21 Jan 2021

Viewed by 2429

Abstract

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that BioTech maintains its standards for the high quality of its published papers [...] Full article

28 pages, 10013 KiB

Open AccessArticle

Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics

by Suriyea Tanbin, Fazia Adyani Ahmad Fuad and Azzmer Azzar Abdul Hamid

BioTech 2021, 10(1), 1; https://doi.org/10.3390/biotech10010001 - 28 Dec 2020

Cited by 78 | Viewed by 6639

Abstract

Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Human hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Alpha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we proposed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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