Fabia Battistuzzi

Fabia Ursula Battistuzzi
Associate Professor
340 DH
(248) 370-3593
Lab location: 335B DH
Lab phone: (248) 370-2658
battistu@www.zhongqiwg.com

Courses:

BIO 3340 Evolutionary Biology
BIO 4340 Principles of Evolutionary Medicine
BIO 4342/5382 Topics in Evolutionary Biology
BIO 4412 Functional Genomics and Bioinformatics
BIO 3343 Earth and Life Co-evolution (field course)

Research: Tempo and mode of microbial life’s evolution

Life as we know it is astoundingly diverse, resilient, and adaptable to virtually any environment on Earth. Yet, the tempo (chronology) and mode (evolutionary mechanisms) of the evolution that gave rise to billions of species are mostly unknown. The aim of Dr. Battistuzzi's research is to understand when and how species have evolved and investigate the connections between their genetic innovations and variations in environmental conditions. Among all species, microbes span the largest duration of Earth history and are extremely metabolically and ecologically diverse. These characteristics make them a powerful resource to investigate evolutionary mechanisms over long (billions of years) and short (millions of years) timescales while tracing the origin of important ecological innovations such as pathogenicity and the origin of infectious diseases. Main projects in her lab include:

• Ancient evolution of prokaryotes. Prokaryotes (Bacteria and Archaea) evolve with complex mechanisms that have hindered a clear understanding of their relationships (phylogeny) and time of origin (molecular clocks). The aim of this research project is to improve our understanding of ancient evolution of prokaryotes and its relation to environmental changes at a planetary scale.
  
  
• Origin and evolution of infectious diseases. Many eukaryotic microbes are pathogenic to humans and other animals causing diseases such as malaria. The antiquity of the origin of these diseases is poorly understood and, consequently, the environmental and ecological circumstances that favored their spread to multiple hosts are highly debated. With this project, I seek to reconstruct the history of microbial pathogens and use this information to investigate their innovations at the genetic level.
  
  
• Assessment and development of bioinformatics tools. The amount of molecular data available and forthcoming requires a re-evaluation of current bioinformatics tools to assess their applicability to very large datasets, the accuracy of their results, and their computational requirements. The goal of this research project is to produce improved guidelines for the use of bioinformatics tools to address established areas of research and develop new tools to answer the needs arising from a growing community of researchers in evolution.

Each one of these independently developed projects pushes the science of bioinformatics forward while their synergistic effects will lead to a deeper understanding of life’s evolutionary history which is fundamental to understanding current and future changes in the biosphere.

选择出版物:

Fabia Battistuzzi NCBI publication list

Powell*, C. and F. U. Battistuzzi. (2020). Quantifying the error of secondary versus distant-primary calibrations in a simulated environment.Frontiers in Genetics11: 252.DOI:10.3389/fgene.2020.00252/full.

Sitto*, F. and F.U. Battistuzzi. (2019). Estimating pangenomes with Roary.Molecular Biology and Evolution:37(3): 933–939. DOI:10.1093/molbev/msz284.

Superson, A.A*, D. Phelan*, A. Dekovich* and F.U. Battistuzzi. (2019). Choice of species affects phylogenetic stability of deep nodes: an empirical example in Terrabacteria.Bioinformatics35(19): 3608-3616. DOI:10.1093/bioinformatics/btz121.

Tao, Q., K. Tamura, F.U. Battistuzzi and S. Kumar. (2019). A machine learning method for detecting autocorrelation of evolutionary rates in large phylogenies.Molecular Biology and Evolution36: 811-824.DOI: 10.1093/molbev/msz014.

Battistuzzi, F.U., Q. Tao, L. Jones*, K. Tamura and S. Kumar. (2018). RelTime relaxes the strict molecular clock throughout the phylogeny.Genome Biology and Evolution10: 1631-1636. DOI:10.1093/gbe/evy118.

Chaudhry, S.*, N. Lwin*, D. Phelan*, A.A. Escalante and F.U. Battistuzzi. (2018). Comparative analysis of low complexity regions inPlasmodia.Scientific Reports8: 335.DOI:10.1038/s41598-017-18695-y.

Marin, F.U. Battistuzzi, A.C. Brown* and B. Hedges. (2018). The timetree of prokaryotes: new insights into their evolution and speciation.Molecular Biology and Evolution34: 437-446. DOI:10.1093/molbev/msw245.

Battistuzzi, F.U., K. Schneider, M.K. Spencer, D. Fisher, S. Chaudhry* and A.A. Escalante. (2016). Profiles of low complexity regions in Apicomplexa.BMC Evolutionary Biology16:47.DOI: /10.1186/s12862-016-0625-0.

*OU student