Achal Dhariwal

• Brar, N.K.; Dhariwal, Achal; Åmdal, Heidi Aarø; Junges, Roger; Salvadori, Gabriela & Baker, J.L. [Show all 8 contributors for this article] (2024). Exploring ex vivo biofilm dynamics: consequences of low ampicillin concentrations on the human oral microbiome. npj Biofilms and Microbiomes. ISSN 2055-5008. 10(1). doi: 10.1038/s41522-024-00507-7.
• Singh, Yogesh; Trautwein, Christoph; Romani, Joan; Salker, Madhuri S.; Neckel, Peter H. & Fraccaroli, Isabel [Show all 17 contributors for this article] (2023). Overexpression of human alpha-Synuclein leads to dysregulated microbiome/metabolites with ageing in a rat model of Parkinson disease. Molecular Neurodegeneration. ISSN 1750-1326. 18(1). doi: 10.1186/s13024-023-00628-1. Full text in Research Archive
• Dhariwal, Achal; Bråten, Lars Christian Haugli; Sturød, Kjersti; Salvadori Da Silva, Gabriela; Bargheet, Ahmed & Åmdal, Heidi Aarø [Show all 11 contributors for this article] (2023). Differential response to prolonged amoxicillin treatment: long-term resilience of the microbiome versus long-lasting perturbations in the gut resistome. Gut microbes. ISSN 1949-0976. 15(1). doi: 10.1080/19490976.2022.2157200.
• Rajar, Polona; Dhariwal, Achal; Salvadori Da Silva, Gabriela; Junges, Roger; Åmdal, Heidi Aarø & Berild, Dag [Show all 12 contributors for this article] (2022). Microbial DNA extraction of high-host content and low biomass samples: Optimized protocol for nasopharynx metagenomic studies. Frontiers in Microbiology. ISSN 1664-302X. 13, p. 1–15. doi: 10.3389/fmicb.2022.1038120. Full text in Research Archive
• Dhariwal, Achal; Junges, Roger; Chen, Tsute & Petersen, Fernanda Cristina (2021). ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data. NAR Genomics and Bioinformatics. ISSN 2631-9268. doi: 10.1093/nargab/lqab018. Show summary

  The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.

• Bissinger, Rosi; Nemkov, Travis; D'Alessandro, Angelo; Grau, Marijke; Dietz, Thomas & Bohnert, Bernhard N. [Show all 25 contributors for this article] (2021). Proteinuric chronic kidney disease is associated with altered red blood cell lifespan, deformability and metabolism. Kidney International. ISSN 0085-2538. 100(6), p. 1227–1239. doi: 10.1016/j.kint.2021.08.024. Full text in Research Archive
• Dhariwal, Achal; Petersen, Fernanda Cristina; Chen, Tsute & Junges, Roger (2021). ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data. NAR Genomics and Bioinformatics. ISSN 2631-9268. 3. doi: 10.1093/nargab/lqab018. Full text in Research Archive
• Singh, Yogesh; Christoph, Trautwein; Dhariwal, Achal; Salkar, Madhuri S.; Alauddin, Md & Zizmare, Laimdota et al. [Show all 19 contributors for this article] (2020). DJ-1 (Park7) affects the gut microbiome, metabolites and development of Innate Lymphoid cells (ILCs). Scientific Reports. ISSN 2045-2322. doi: 10.1038/s41598-020-72903-w. Full text in Research Archive
• Dhariwal, Achal; Junges, Roger; Chen, Tsute & Petersen, Fernanda Cristina (2020). ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data. bioRxiv. ISSN 2692-8205. doi: 10.1101/2020.08.14.250837.
• Soni, Nancy; Hegde, Niranjan; Dhariwal, Achal & Kushalappa, Ajjamada C. (2020). Role of laccase gene in wheat NILs differing at QTL-Fhb1 for resistance against Fusarium head blight. Plant Science. ISSN 0168-9452. 298. doi: 10.1016/j.plantsci.2020.110574.
• Sturød, Kjersti; Dhariwal, Achal; Dahle, Ulf R; Vestrheim, Didrik Frimann & Petersen, Fernanda Cristina (2019). Impact of narrow-spectrum penicillin V on the oral and faecal resistome in a young child treated for otitis media. Journal of Global Antimicrobial Resistance. ISSN 2213-7165. 20, p. 290–297. doi: 10.1016/j.jgar.2019.08.004. Full text in Research Archive
• Khan, Nargis; Dhariwal, Achal; Mendonca, Laura; Fontes, Ghislaine; Dick, Menzies & Xia, Jianguo et al. (2019). Intestinal dysbiosis compromises alveolar macrophage immunity to Mycobacterium tuberculosis. Mucosal Immunology. ISSN 1933-0219. doi: 10.1038/s41385-019-0147-3.
• Dhariwal, Achal; Chong, Jasmine; Habib, Salam; King, Irah L.; Agellon, Luis B. & Jianguo, Xia (2017). MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Research (NAR). ISSN 0305-1048. 45, p. W180–W188. doi: 10.1093/nar/gkx295.

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• Dhariwal, Achal; Petersen, Fernanda Cristina; Chen, Tsute & Baker, Jonathon (2023). Introduction to Resistome: key concepts and hands-on analysis.
• Brar, Navdeep Kaur; Dhariwal, Achal; Junges, Roger; Håkansson, Anders & Petersen, Fernanda Cristina (2022). Potential of HAMLET, a human milk protein-lipid complex, to modulate ecological changes in the oral microbiome induced by amoxicillin.
• Rajar, Polona; Dhariwal, Achal; Salvadori, Gabriela ; Junges, Roger; Åmdal, Heidi Aarø & Berild, Dag [Show all 12 contributors for this article] (2022). Microbial DNA extraction of high-host content and low biomass samples: optimized protocol for nasopharynx metagenomic studies. Show summary

  Low microbial biomass and high human DNA content in nasopharyngeal aspirate samples hinder comprehensive characterization of microbiota and resistome. We obtained samples from premature infants, a group with increased risk of developing respiratory disorders and infections, and consequently frequent exposure to antibiotics. Our aim was to devise an optimal protocol for handling nasopharyngeal aspirates from premature infants, focusing on host DNA depletion and microbiome and resistome characterization. Three depletion and three DNA extraction protocols were compared, using RT-PCR and whole metagenome sequencing to determine the efficiency of human DNA removal, taxonomic profiling and assignment of antibiotic resistance genes. Protocols were tested using mock communities, as well as pooled and individual patient samples. The only extraction protocol to retrieve the expected DNA yield from mock community samples was based on a lytic method to improve Gram positive recovery (MasterPure™). Only samples depleted with MolYsis™ showed satisfactory, but varied reduction in host DNA content, in both pooled and individual patient samples, allowing for microbiome and resistome characterisation (host DNA content from 15% to 98%). PCR results were indicative of achieved microbial enrichment. Despite high human DNA and low microbial biomass content in nasopharynx aspirates of preterm infants, we were able to reduce host DNA content to levels compatible with downstream shotgun metagenomic analysis, including bacterial species identification and coverage of antibiotic resistance genes. Whole metagenomic sequencing of microbes colonizing the nasopharynx may contribute to explaining the possible role of airway microbiota in respiratory conditions and reveal carriage of antibiotic resistance genes.

• Dhariwal, Achal & Petersen, Fernanda Cristina (2022). Using ResistoXplorer for comprehensive visual, statistical, and exploratory analysis of AMR metagenomic data .
• Dhariwal, Achal (2022). Impact of Long-Term Amoxicillin Treatment on the Gut Microbiome and Resistome.
• Dhariwal, Achal & Petersen, Fernanda Cristina (2022). ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data.
• Dhariwal, Achal & Petersen, Fernanda Cristina (2022). Impact of Long-Term Amoxicillin Treatment on the Gut Microbiome and Resistome.
• Brar, Navdeep Kaur; Dhariwal, Achal; Åmdal, Heidi Aarø; Junges, Roger; Salvadori, Gabriela & Petersen, Fernanda Cristina (2022). The Impact of Ampicillin on the Oral Microbiome and Resistome.
• Dhariwal, Achal & Petersen, Fernanda Cristina (2021). Resistoxplorer: A web-based tool for visual, statistical and exploratory analysis of resistome data.
• Petersen, Fernanda Cristina; Dhariwal, Achal; Bråten, Lars Christian Haugli; Sturød, Kjersti; Junges, Roger & Salvadori, Gabriela [Show all 10 contributors for this article] (2021). Off-target impact of long-term amoxicillin treatment.
• Dhariwal, Achal; Petersen, Fernanda Cristina; Junges, Roger & Chen, Tsute (2020). ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data.
• Petersen, Fernanda Cristina; Dhariwal, Achal; Sturød, Kjersti & Nickelsen, Trine (2020). Babyer får penicillin ? og uheldige bakterier blusser opp. [Internet]. Apollon.
• Chen, Tsute & Dhariwal, Achal (2019). Analysis of microbiome data.
• Dhariwal, Achal; Junges, Roger & Petersen, Fernanda Cristina (2019). Exploratory analysis and Visualization of resistome data. Show summary

  Abstract: Recently, antimicrobial resistance (AMR) has gained everybody’s attention at a global level due to its impact on public health. Nation-wide surveillance efforts have been going on for characterization of these resistance determinants responsible for AMR. Due to advancements in metagenomics, comprehensive databases have been already established providing hierarchical information such as class, group and mechanism of these antibiotic resistance genes (ARGs). Additionally, some recently developed tools are also able to quantify the abundance of these ARGs present in any metagenomic sample. However, it is still challenging to perform bioinformatics analysis and interpretation of such data. Further, there is no such specific tool developed to support comprehensive downstream analysis and visualization from resistome data. As a result, we are aiming to develop ResistoAnalyst, a user-friendly web-based tool that integrates recent advancements in visualization and statistics techniques, integrated with several comprehensive databases, to enable comprehensive analysis of resistome data generated from metagenomics studies. Development of such tool will enable most clinicians, bench researchers to better understand, and generate hypothesis from their own data in real time. Additionally, ResistoAnalyst will be a valuable resource for sequence-based surveillance and monitoring of antibiotic usage and resistome development.

• Dhariwal, Achal & Petersen, Fernanda Cristina (2019). Visual exploration and network-based analysis of resistome data.
• Dutta, Anirban; Dhariwal, Achal; Nangia, Sushma & Mande, Sharmila (2018). Development and validation of comprehensive ‘perinatal risk factors based clinical score' for management of early onset neonatal sepsis in preterm neonates less than 35 weeks gestation -a prospective observational study. Show summary

  Participants from the "Born in the Twilight" team Dr. Sushma Nangia, LHMC Mr. Achal Dhariwal, Univ. of Oslo Dr. Sharmila Mande, TCS Dr. Anirban Dutta, TCS Growing resistance to antimicrobial drugs in pathogenic microorganisms has become the most important problems of 21st century. In a recent report it is estimated that approximately 0.7 million people die every year from drug resistant strains of microbes. The number will increase to 10 million by 2050, surpassing cancer (8.2 million deaths per year). Strengthening surveillance systems for combatting Antimicrobial Resistance (AMR) is an urgent and contemporary challenge. The Indian Council for Medical Research, Delhi, India in collaboration with the Department of Informatics, University of Oslo, Norway and their partner HISP India is organizing a workshop for designing the Framework for development of an integrated surveillance system for AMR. WORKSHOP DATES and Venue - November 12th and 13th, 2018, ICMR, New Delhi. This 2-day workshop is an Indo-Norwegian initiative to brainstorm and conceptualize the way forward to design and develop a framework for an integrated AMR surveillance system, bringing together data from sources related to humans, climate and animal sources. The workshop will bring in experts from various domains of AMR (Humans, Animals and Climate), along with those in digital health technologies. Together, we will brainstorm to help develop an initial roadmap for the development of a One health network for the AMR surveillance.

• Dhariwal, Achal & Petersen, Fernanda Cristina (2018). Network-based analysis of Resistome data.
• Dhariwal, Achal (2018). Statistical, Visual and Functional Analysis of Microbiome Data. McGill University.

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