Microbial Diversity

What should a scientist look like? A pair of articles was published this morning in our local paper ( the Herald Times ).  In it are details of the many inequities faced by female scientists at Indiana University.  In those articles, some startling statistics were published, including the percentage of female faculty in the sciences at IU (~10%) and directly relevant to me, the inequity in salary (in Biology, the seven female full professors make ~$131,000 while the 22 male full professors make ~161,000).  In addition, there were some poignant anecdotes from female professors: "I never had children" said one, "I or my partner. We never had time we could take out of our careers without feeling like we might lose what we had gained."   It's nigh time to address the root of this insidious problem.  It cannot be fixed by hiring more women -- there are few of us to begin with and additionally, we all agree we want to hire both the  best and most  diverse  faculty (s

An intriguing title for an article published in PLoS Pathogens on Halloween.  Needless to say, many of us in the Wolbachia community anxiously await the discovery of the mechanism behind Cytoplasmic Incompatibility.  For those of you who aren't Wolbachia -philes, the short of it is that this bacterium has figured out a nifty way to spread through insect populations. First, it's transmitted via the germ line -- so that means eggs come pre-loaded with Wolbachia from infected mothers.  Second, Wolbachia affect reproduction in a variety of ways but the most common is that infected females can mate with uninfected or infected males.  However, if you are an uninfected female -- if you don't carry the bacterium -- you cannot mate with infected males.  This drops the fecundity of uninfected females and allows Wolbachia , and the host carrying it, to spread.  There are also some interesting incompatibilities that result when hosts are infected with two different Wolbachia  -- so

The NSF Doctoral Dissertation Improvement Grant deadline is almost upon us (October 10, 2013).  What is funded by the DDIG FOA? From the NSF website: “Allowable items include travel to specialized facilities or field research locations and professional meetings, use of specialized research equipment, purchase of supplies and services not otherwise available, the hiring of field or laboratory assistants, fees for computerized or other forms of data, and rental of environmental chambers or other research facilities.”  Importantly, you CANNOT use the DDIG funds for stipends or tuitions. Note:  If your PI already has a grant on this topic, you are not likely to be funded; If “existing funds” are available for the proposed work, you are disqualified.  The important point being that these proposals are used to gauge the independence of the PhD candidate from the PI’s major research thrust. Why else consider writing a DDIG? The fame …The glory…The practice and most

There have been some interesting, thought provoking publications of late concerning the last vestiges of "sterility" if you will, with regards to bacterial colonization.   Remember back when folks thought the healthy lung was sterile? Yeah, out the window with that hypothesis (see  here , and  here ).  Remember urine being sterile? Nope, you must've missed this and this .  Is nothing sacred, people! Are bacteria truly everywhere![1] In their publication, "Mother knows best: the universality of maternal microbial transmission" , Seth Bordenstein and his student Lisa Funkhouser review for us the evidence in support of the vertical transmission strategy for host-associated bacteria.  While the invertebrates are undoubtedly best known for maternal transmission ( the vent giant clams from my youth are highlighted by Funkhouser and Bordenstein as are the pea aphids), they present the evidence currently in hand to support a decidedly unsterile environment in utero.

Just submitted our first paper to PeerJ - the awesome new, open access journal aimed at tipping the entire publishing establishment on its head.  I'm looking forward to a smooth review process -- hopefully as sleek and helpful as the submission process. <UPDATE: our paper was accepted.  I will post a link to the paper once it's online!> Our manuscript presents PhyBin, a computer program aimed at binning precomputed sets of trees in Newick format, a file format produced by the majority of tree building software.  As we assert in the manuscript, PhyBin is a utility rather than a complete solution; it can serve as a component in many genomics pipelines, and provides a useful addition to the landscape of tools for dissecting and visualizing large numbers of trees.  After the user applies their chosen ortholog prediction and tree-building algorithms, PhyBin offers a quick way to visualize and browse the different evolutionary histories, either binned by topology and sorted b

I recently heard some interesting 2nd hand advice from Matt Welsh , whose blog has plenty of advice/rants/raves for tenure track junior faculty.   Matt ended up leaving academia for Google but with regards to writing grants and getting funding, he's said "Focus on writing papers, send out proposals like farts in the wind"; basically, spam granting agencies without a lot of thought. For some reason this really bothers me.  It is effectively concluding that grantsmanship and actual intellectual merit cannot be accurately measure by the review process, that funding is effectively a crapshoot and you just need to play the game lots and lots in order to get funded.   It's succumbing to the view that folks reviewing your proposals are not going to know much about your area or understand the significance. Papers, on the other hand, tend to be reviewed by researchers more close to your area of expertise and this is where you need to spend your time polishing and honing your

This is a continuation of my blog post yesterday concerning a recent NIH section meeting.  I was there as an Early Career Reviewer -- a great opportunity to learn about the process and listen in on the discussions.  While most reviewers get assigned many more, I was assigned only 4 applications to review. This gave me plenty of time to listen to what folks were saying and really pay attention to the conversation going on about applications being discussed.  Each application gets between 30-10 minutes of discussion (depending on time of day, enthusiasm or discordance among reviewers, etc). Not much can be generalized across all applications we reviewed.  However, in the R01 category , I think several general pieces of advice can be gleaned - at least in the GVE context - with regards to what works an what doesn't (FYI, R01's are those large, major awards -- after you get one of these, you are no longer a "new investigator").   Note: Although the names of panelis

I've often wondered what it is like on an NIH study section, and how it differs from an NSF panel, so I happily agreed to serve this past week on my first Genetic Variation and Evolution (GVE) study section.   What is an NIH study section like?  Well, on the face of it, much like an NSF panel.  Before you come to the meeting, you are given a set of applications to review.  Like the NSF, your review of each individual application is based on certain criteria and you are asked to comment on these criteria.  In an NSF review you first score the proposal (Excellent, Very Good, Good, Fair, or Poor).  At NSF, criteria you should comment on or focus on in your review are "Intellectual Merit" and "Broader Impacts" (with strengths and weaknesses for each).   You also give a summary statement at the end of your review that should reflect your score.  For the NIH, the scored criteria are "Significance", "Investigator", "Innovation&quo

A recent publication by RT Jones, L.G. Sanchez, and N Feirer: "A cross-taxon analysis of insect-associated bacterial diversity" started me thinking about how we sample insects.  You can see the article here at PLoSONE: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0061218 In this publication, the authors perform a large collection of diverse insects and then subsequently a 16S rRNA gene amplicon analysis.  They use the V1-V2 region and 454 pyrosequencing.  They use whole insects as the source of material for the DNA extractions and perform a set of bioinformatics processing steps downstream in an attempt to reduce artifacts that may lead to inflation of diversity estimates in their samples.   From their published methods, this seems to be the order in which reads were processed: 1.    Reads are truncated (to compare across the same 16S positions) and removed “low quality reads” using QIIME’s default settings – I am not sure if ampli