| Title |
Leveraging ecological theory to guide natural product discovery
|
|---|---|
| Published in |
Journal of Industrial Microbiology & Biotechnology, March 2016
|
| DOI | 10.1007/s10295-015-1683-9 |
| Pubmed ID | |
| Authors |
Michael J Smanski, Daniel C Schlatter, Linda L Kinkel |
| Abstract |
Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 75% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| India | 1 | 1% |
| Unknown | 88 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 23% |
| Researcher | 18 | 20% |
| Student > Master | 10 | 11% |
| Student > Bachelor | 5 | 5% |
| Other | 5 | 5% |
| Other | 15 | 16% |
| Unknown | 18 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 39% |
| Biochemistry, Genetics and Molecular Biology | 12 | 13% |
| Chemistry | 11 | 12% |
| Computer Science | 4 | 4% |
| Immunology and Microbiology | 3 | 3% |
| Other | 6 | 7% |
| Unknown | 20 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 October 2015.
All research outputs
#14,915,476
of 25,374,917 outputs
Outputs from Journal of Industrial Microbiology & Biotechnology
#1,215
of 1,612 outputs
Outputs of similar age
#151,149
of 312,601 outputs
Outputs of similar age from Journal of Industrial Microbiology & Biotechnology
#11
of 27 outputs
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So far Altmetric has tracked 1,612 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.