Alm:Publications: Difference between revisions

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==Reviewed Journal Publications==
==Reviewed Journal Publications==


'''Dana E. Hunt*, Lawrence A. David*, Dirk Gevers, Sarah P. Preheim, Eric J. Alm, Martin F. Polz (2008) Resource Partitioning and Sympatric Differentiation Among Closely Related Bacterioplankton, ''Science'' (in press)'''
'''Dana E. Hunt*, Lawrence A. David*, Dirk Gevers, Sarah P. Preheim, Eric J. Alm, Martin F. Polz (2008) Resource Partitioning and Sympatric Differentiation Among Closely Related Bacterioplankton, ''Science'' (in press)''', '''*''' = these authors contributed equally
\* - these authors contributed equally


* Identifying ecologically differentiated populations within complex microbial communities remains challenging, yet is critical for interpreting the evolution and ecology of microbes in the wild. Here, we describe spatial and temporal resource partitioning among Vibrionaceae strains coexisting in coastal bacterioplankton. A quantitative model (AdaptML) establishes the evolutionary history of ecological differentiation, thus revealing populations specific for seasons and lifestyles (combinations of free-living, particle, or zooplankton associations). These ecological population boundaries frequently occur at deep phylogenetic levels (consistent with named species); however, recent and, perhaps, ongoing adaptive radiation is evident in Vibrio splendidus, which comprises numerous ecologically distinct populations at different levels of phylogenetic differentiation. Thus, environmental specialization may be an important correlate or even trigger of speciation among sympatric microbes.  
* Identifying ecologically differentiated populations within complex microbial communities remains challenging, yet is critical for interpreting the evolution and ecology of microbes in the wild. Here, we describe spatial and temporal resource partitioning among ''Vibrionaceae'' strains coexisting in coastal bacterioplankton. A quantitative model ([http://almlab.mit.edu/ALME/Software/Software.html AdaptML]) establishes the evolutionary history of ecological differentiation, thus revealing populations specific for seasons and lifestyles (combinations of free-living, particle, or zooplankton associations). These ecological population boundaries frequently occur at deep phylogenetic levels (consistent with named species); however, recent and, perhaps, ongoing adaptive radiation is evident in ''Vibrio splendidus'', which comprises numerous ecologically distinct populations at different levels of phylogenetic differentiation. Thus, environmental specialization may be an important correlate or even trigger of speciation among sympatric microbes.  




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'''Shapiro BJ, Alm EJ (2008) Comparing Patterns of Natural Selection across Species Using Selective Signatures. [http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0040023 ''PLoS Genetics'' 4(2): e23 doi:10.1371/journal.pgen.0040023] pmid: 18266472
'''Shapiro BJ, Alm EJ (2008) Comparing Patterns of Natural Selection across Species Using Selective Signatures. [http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0040023 ''PLoS Genetics'' 4(2): e23 doi:10.1371/journal.pgen.0040023] pmid: 18266472'''
'''
 
* Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 γ-proteobacterial species. We describe the pattern of fast or slow evolution across species as the “selective signature” of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in ''Idiomarina loihiensis'', mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell.
* Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 γ-proteobacterial species. We describe the pattern of fast or slow evolution across species as the “selective signature” of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in ''Idiomarina loihiensis'', mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell.



Revision as of 08:37, 6 May 2008

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Publications

Reviewed Journal Publications

Dana E. Hunt*, Lawrence A. David*, Dirk Gevers, Sarah P. Preheim, Eric J. Alm, Martin F. Polz (2008) Resource Partitioning and Sympatric Differentiation Among Closely Related Bacterioplankton, Science (in press), * = these authors contributed equally

  • Identifying ecologically differentiated populations within complex microbial communities remains challenging, yet is critical for interpreting the evolution and ecology of microbes in the wild. Here, we describe spatial and temporal resource partitioning among Vibrionaceae strains coexisting in coastal bacterioplankton. A quantitative model (AdaptML) establishes the evolutionary history of ecological differentiation, thus revealing populations specific for seasons and lifestyles (combinations of free-living, particle, or zooplankton associations). These ecological population boundaries frequently occur at deep phylogenetic levels (consistent with named species); however, recent and, perhaps, ongoing adaptive radiation is evident in Vibrio splendidus, which comprises numerous ecologically distinct populations at different levels of phylogenetic differentiation. Thus, environmental specialization may be an important correlate or even trigger of speciation among sympatric microbes.


Dylan Chivian, Eric J. Alm, and 17 others, Onstott TC (2008) Environmental genomics reveals a single species ecosystem deep within the Earth. Science (in press)

  • DNA from 2.8 km deep in the Earth’s crust reveals the genetic complement necessary for a single species ecosystem.


Shapiro BJ, Alm EJ (2008) Comparing Patterns of Natural Selection across Species Using Selective Signatures. PLoS Genetics 4(2): e23 doi:10.1371/journal.pgen.0040023 pmid: 18266472

  • Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 γ-proteobacterial species. We describe the pattern of fast or slow evolution across species as the “selective signature” of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in Idiomarina loihiensis, mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell.


Alm E, Huang K, Arkin A (2006) The evolution of two-component systems in bacteria reveals different strategies for niche adaptation. PLoS Comput Biol. 2006 Nov 3;2(11):e143

  • Pathways containing histidine protein kinases (HPKs) represent a key mechanism for signal transduction, especially in bacteria. These systems help cells to sense and respond to their environment by detecting external cues and effecting internal responses such as changes in gene expression. As such, they are believed to play a key role in niche adaptation, yet their evolution is difficult to study due to the large number of paralogous subfamilies. This work extends previous large-scale gene evolution studies by considering complex paralogy relationships, and uncovers an abundance of horizontal transfers, gene duplications, and domain shuffling that have marked the evolutionary history of HPKs. An important finding of this study is qualitative differences between the main strategies for acquiring new HPKs (horizontal gene transfer and gene duplication). Hallmarks of the latter process include domain shuffling and the generation of “orphan” HPKs not co-transcribed with a cognate response regulator.


Price MN, Arkin AP, Alm EJ (2006) The life-cycle of operons. PLoS Genetics 2006 Jun;2(6):e96

  • In bacteria, adjacent genes are often transcribed together in operons. Which genes are placed together in operons varies greatly across bacteria. This diversity of operon structure can be used to predict the function of genes: genes that are sometimes in an operon are likely to have related functions, even if they are transcribed separately in the organism of interest. However, it has not been clear why this diversity exists or what its consequences are. This work reconstructs evolutionarily recent changes to operon structures in the well-studied bacterium Escherichia coli. Changes in operon structure are shown to be associated with changes in gene expression patterns, so the diversity in operon structure may reflect adaptation to differing lifestyles. Indeed, some of these changes appear to be beneficial to the organism. This work also reconstructs the molecular mechanisms of operon evolution. Understanding these mechanisms should aid other analyses of bacterial genomes. For example, new operons often arise by deleting the DNA between functionally unrelated genes that happen to be near each other. Thus, recently evolved operons should not be used to infer their genes' function. Overall, this work provides a framework for understanding the evolutionary life-cycle of operons.