Microbiome - How important are the sample space and it's structure?

Another great talk from the symposium on probabilistic microbial modeling...


TLDW Highlights...and links to further reading, term definitions, concept reads and their upcoming workshop etc...

Microbiome abundance or relative abundance...that is the question?!

Really great talk by Shayamal Peddada about metrics for measuring and comparing abundance/relative abundance within and between microbiome samples.

Worth a watch!

For those TLDW (too long didn't watch)...

MICROBE 2018 WrapUp - a note about Mentorship...

Disclaimer! This is a lengthy one!

25 blogs later, ASM Microbe 2018 was a jam packed conference for me! These meetings are blessings and curses because there is so much awesome stuff to see and listen to and not enough time to 'do it all'. But I am always excited when I am able to participate.

If you liked this series, I have other series posted as well, feel free to follow the blog and you'll get notified when I start posting again...hopefully. Before I sign off and my blog goes dark (until my next 'learning adventure') I wanted to take a moment to chat about mentorship.

It's challenging, being a woman in science.
It's challenging, being a minority in science.

It's difficult to get funding for everyone, especially new investigators. You have to have a track record before you can apply for funding and yet you cannot develop that track record easily without funding. It's like being offered a packaged up pair of shiny new scissors and then realizing you NEED a pair of scissors to open the package to begin with... *facepalm*

MICROBE 2018 recap - Microbial Ecology: Theory, XenoGI and Nanoarchaea!

So the final session I attended I was really excited about because it's a blast from my PhD past, jumping back into microbial ecology theory and extremophiles!

Eugene Koonin from NCBI started off the session discussing complexity and simplicity in the genomic era.

"No one can properly define complexity [and yet] we know it when we see it."

• When we look at gene families, we find that 70-80% of genes in prokaryotic genomes are evolutionarily conserved, belong to COGs, are apart of orthologous lineages and can be considered 'distinct evolutionary units'.
• The rest we call ORFans - comprising 10-15% of genes within a genome. These can either be 'real' or errors in annotation.
• As you increase phylogenetic distance you begin to see a decay in gene content similarity
• Simplicity is 'genome streamlining'
• Complexity is 'gene accumulation'
• Larger effective population sizes are going to limit complexity due to strong selection which will lead to genome streamlining.

To learn more about Koonin's work, check out below and also his google scholar profile:

• Genomes and Protein Universe
• Orthologs, paralogs and evolutionary genomics.
• Computational methods for gene orthology inference
• Functional and evolutionary implications of gene orthology

MICROBE 2018 recap - Evolution of Tuberculosis

https://me.me

So it's Sunday...the meeting started Thursday night. Usually about this time, depending on how ambitious your schedule for the meeting, you are starting to get a little peek'ed and the sessions are starting to run together. For me - a good deal of money is spent coming to these conferences so I have a tendency to pack my schedule. This often times ends in overlapping sessions necessitating a cost/benefit analysis of whether I should risk missing the beginning of the next talk by running to the session after this one or stay in this session and listen to a talk that is perhaps less "soul-on-fire" interesting for me. In either case, you start tapping your coffee IV to make sure it's running only to realize that by this point you've probability built up a super human caffeine tolerance. Yet you still grab that cup and hold it at the morning sessions with such care and possessiveness you would think it a pot of gold.

So major kudos to Caitlin Pepperell and her ability to recapture my attention as my first coffee wore off and I started in on coffee #2. It helps that my next favorite bug - after Vibrio, is Mycobacteria

Evidence I stayed awake...the whole time:

You can decipher my notes above or just read the recap below.

MICROBE 2018 recap - Ancient Infectious Disease - Paleomicrobiology

So for this session and the rest of the meeting my laptop decided it no longer wanted to hold a charge so I was relegated to using old school methods of taking notes...my notebook and a pen! Gasp.

http://theoatmeal.com/comics/pens

Didier Raoult, Faculte de Medecine; IHU Mediterranee Infection
Paleomicrobiology: Human Infections and Antiquity

"Everything was called plague back then..."

There was the Thucidides plague in Athens, the Antonine plague, Justinian plague, Black Death,then the post Columbian era syphilis and 'eruptive fever' (measles and smallpox) followed by the great wars and lice; Douai (18th century), Napoleon (19th century), WWI in the 20th century and the Bolshevic revolution.

Needless to say there's a lot of disease in our human history leaving an indelible mark...that we can find in frozen tissues, fixed tissues, mummies, bone and teeth. The most popular technique or perhaps the most used methodology you would start with in detection of pathogens is PCR.

MICROBE 2018 recap - Jumping back into AMR for a moment...

As you can probably tell I attempted to hop into as many AMR sessions as possible as that is a primary interest of mine...

So before we finish off this blog series on some ancient infectious disease and microbial ecology (upcoming...) let's hop back in briefly to Dr. Lance Price's talk and hit some of his highlighted points.

Lance Price, George Washington University
Expanding our view of zoonotic pathogens: How genomics is revealing insidious host jumps and AMR transmissions

• So we've heard a lot about E. coli ST131 this meeting - it's broad host range, extensive resistance and wide geographic dispersal globally.
• So in thinking about these AMR pathogens spread particularly in E. coli were learn this a lot of overlap of these E. coli STs (isolates) within the meat market and clinic. They have their own clusters, but there is also overlap.
• Through phylogenetic analysis of different STs of E. coli we find both human and 'meat' clade ancestors suggesting independent host jumps.
• ST10 and ST38: ancestor in meat, yet found in clinical isolates
• ST12 found to have humans as the ancestor but has been found in food animal production isolates
• But it's not just limited to human <> meat...enter poultry, APEC and the ColV plasmid
• ST95 has a human ancestor, has been found in meat and isolates have been obtained from poultry falling into ST95 characterized as APEC (Avian Pathogenic E. coli). So there is potential for human isolates moving into poultry, acquiring plasmid then spilling back over into humans and meat.
• ST117 has been an emerging APEC problem in poultry but there is evidence of spillover into humans and in food production animals (meat) and is causing sporadic spread.

So policy? Given the expanding issue of these isolates many with AMR in our food animal production line... what is being done?

California has now restricted use of antibiotics in animals.
(the actual senate bill if you are interested, SB27)

• This is all good but in the event that these jumps have already occurred and establishment of these AMR strains has happened in humans. Legislation of this sort will have little effect.
• BUT it does have the potential, if followed long enough, for 'washing out' of sporadic spreaders.

From post about Canada's growing problem of antibiotic resistant bacteria being found in meat
and there being less food inspection agents. (https://eatinggreener.wordpress.com/tag/antibiotics/)

MICROBE 2018 recap - Tales of Biogas Core Microbial Communities: The Research, The Rant, The Learning Process

"Research is easy! You have your hypothesis, your starting point, experimentation, perhaps some optimizations and options you take along the way followed by results, analysis and whalah, you are done and have forever changed the world..."

... SAID NO ONE EVER!

Here's an example from a mathematical modeling of infectious disease class I took several years back while still in grad school.

The plan:

Everything goes smoothly...splendidly even, and we all take tea breaks as our analyses run seamlessly without errors or missing/wrongly formatted data leading to a totally understandible, interpretable results that confirms all our hypotheses...

Reality:

By the end, I think we all just wanted a stiff drink.

And this is research! 

The glory and terribleness of it - it's exciting, frustrating and above all a learning process.

MICROBE 2018 recap - Tiny Drivers of Evolution - HGT in Microbes

Dr. Michael Brockhurst, University of Sheffield
Causes and consequences of horizontal gene transfer (HGT) in microbes

We are now in the world of temperate phages...and one plasmid that we'll hear about later.

• Temperate phages have a two-stage life cycle, lytic and lysogenic (where they 'hide' by integrating in the genome and becoming a prophage).
• So what are the benefits of interacting and integrating temperate phages as a bacterium?
• Lots of horizontal gene transfer
• Accelerated evolutionary adaptation potential - how so?
• When you have phages jumping in and out of genomes leaving and taking DNA with them, you have the potential for mutational events and rearrangements...genes get turned on and off - this is all fuel for evolutionary adaptation (or just death, ya death can happen too).
• Increased competitiveness

Story Time...

MICROBE 2018 recap - Antibiotics and Evolution of Resistance - Poster Talk Take Home Messages

So another round of Poster Talks, this time on Antibiotic Resistance...let's boil these posters down to their take home messages and provide some links for further information!

Anna Seekatz - University of Michigan
Longitudinal impact of prophylactic antibiotic use on the gut microbiota and antimicrobial
resistance genes

Methods: 

• Use of cefazolin, clindamycin, vancomycin
• Up to 7 stool samples collected before and after antibiotic administration
• 16S rRNA gene sequencing
• qPCR to identify antibiotic resistance genes
• Mixed model analysis

THM: "While ultimately your gut microbiota does 'drift' away from itself over time, a short pulse of antibiotics DOES produce a discernable 'bump' in the population composition immediately following antibiotic administration"

Further Reading:

• Seekatz, Anna Maria, and Vincent Bensan Young. "Clostridium difficile Infection and the Tangled Web of Interactions Among Host, Pathogen, and Microbiota." Gastroenterology 154.6 (2018): 1573-1576.
• Francino, M. P. "Antibiotics and the human gut microbiome: dysbioses and accumulation of resistances." Frontiers in microbiology 6 (2016): 1543.
• Shreiner, Andrew B., John Y. Kao, and Vincent B. Young. "The gut microbiome in health and in disease." Current opinion in gastroenterology 31.1 (2015): 69.
• Jakobsson, Hedvig E., et al. "Short-term antibiotic treatment has differing long-term impacts on the human throat and gut microbiome." PloS one 5.3 (2010): e9836.
• Raymond, Frédéric, et al. "The initial state of the human gut microbiome determines its reshaping by antibiotics." The ISME journal 10.3 (2016): 707.

MICROBE 2018 recap - Microbes that Know No Borders - Zoonoses and "One Health"

Welcome to Tanzania...land where most patients entering the hospital for fever are treated empirically for malaria and there is a poor clinical response to antimalarial drugs.

Why might patients have poor antimalarial response and high case fatality rates?

MICROBE 2018 recap - Microbes that Know No Borders - Emergence and Transmission

Dr. Julian Parkhill, Sanger Institute
Signatures of emergence and transmission in bacterial pathogens

Dr. Parkhill has been involved on analysis of transmission and emergence of pathogens for almost 2 decades now. A glance through his publication record shows involvement in epidemic analysis and antimicrobial resistance in Burkholderia, Campylobacter, Neisseria, Legionella, Cholera, Mycobacteria and has assisted in the development of tools and analysis for better visualization and annotation of sequence data, faster phylogenetic analysis, whole genome sequencing, SNPs and AMR, population structure and much more.

Today we looked at Extraintestinal Pathogenic E. coli (ExPEC) and Uropathogenic E. coli (UPEC), and once again we are looking at ST131 in particular as we did in the AMR Highlights blog.

• ST131 clones are said to have emerged in 2000, sequentially acquiring fluoroquinolone resistance followed by beta-lactam resistance (blaCTXM15), rapidly expanded and have remained stable ever since in terms of population size.

But is this really 'emergence'?

MICROBE 2018 recap - Microbes that Know No Borders - AMR, Humans and Animals

Dr. Susan Sanchez is from the College of Veterinary Medicine at the University of Georgia. She is the section head for Microbiology and Molecular Biology, the Assistant Director of the Biomedical Health Science Institute and the Chair of One Health.

Her research interests include: (i) Antimicrobial resistance (AMR) spread in humans and animals (ii) Staphylococcus and Salmonella with a focus on MRSA and (iii) Diagnostic testing for zoonses present in animals.

Her talk focused on how AMR spreads between humans and animals. Interestingly she started off by saying her adviser had said a long time ago that clinical microbiology is dead, we have antimicrobials. I think we can all agree, that is not true. Estimates suggest that a failure to address AMR could lead to 10 million deaths by 2050.

MICROBE 2018 - A moment to appreciate Art, Anecdotes, Imagination and Stress Poop...

Taking a brief break to appreciate the imaginative and artistic side of the ASM General meeting...

1990s-esk Viewmaster! 

The vendors were out in full force with creative ways of drawing in the crowd including video games where you shoot microbes, lots of spin the wheels, scavenger hunts followed by a claw game and of course throw backs to the childhoods of many of the attendees such as Karius...

There were plenty of buttons to collect throughout the conference as you made your way through the exhibition hall listening to poster talks, viewing posters and perusing vendors. You could easily establish your pen collection for the next year and giant microbes are always a staple in many of the vendor give aways (red blood cell via Eppendorf) and Chicken Pox via ATCC.

In the world of art both Trilobite Glassworks and Artologica were in attendance as well.

HIV magnet - Trilobite Glassworks

ComputerPhage - Trilobite Glassworks.
Also featured, several stickers courtesy of
ASM and other vendor booths

The computerphage by Trilobite Glassworks was made almost entirely of computer parts salvaged by her husband. Given my husband is a software engineer I thought he'd get a kick out of that.

MICROBE 2018 recap - AMR in the Americas, Highlights

Highlights from the Session:

Surveillance of Antibacterial Resistance in the Americas

Mariana Castanheira, JMI Laboratories and the SENTRY Program

• The SENTRY program was established in 1997 and is one of the longest running antimicrobial surveillance programs globally. Check out their website for more information and access to visualizations of their surveillance. One of the things I note is the obvious need for AMR surveillance in Africa and parts of the middle east where I see by their map much data is missing/lacking.
• Some major sequence types to keep a close eye on with respect to growing and expanding resistance in the Americas (especially Latin America) include E. coli ST131 and K. pneumoniae ST258.
• When interrogating genes for resistance in E. coli and K. pneumoniae it was found that diversity within resistance encoding genes was higher in E. coli than K. pneumoniae. 
• 0.5% of E. coli have been found resistant to Colistin
• 2.3% of K. pneumoniae have been found resistant to  Colistin
• mcr1 was found in E. coli while K. pneumoniae appeared to multiple mechanisms and genes involved conferring colistin resistance including mcr1, mrgB disruption or alteration, and pmrB.
• A. baumannii has show increasing resistance profiles within Latin America when 1997-2000 was compared to 2013-2016. Rises were seen in resistance to:
• Meropenem (18.4% to 86.3%) 
• Levofloxacin (76.9% to 87.6%)
• Amikacin (77.3% to 82.4%)
• Ampicillin-sulbactam (70.7% to 83.6%)
• Colistin (0.8% to 3.4%).
•  Of note: Susceptible and resistant isolates have been shown to have the same pattern of expression of their resistance encoding genes so you cannot use that as a marker of organisms 'resistance'. 

MICROBE 2018 recap - Bioinformatics - PhaME: from Reads to Genomes to SNP phylogenies and more...

Karen Davenport, LANL:

From Raw Reads to  Trees: Whole Genome Single Nucleotide Polymorphisms Phylogenetics Across the Tree of Life

This presentation may win for longest title.

So Los Alamos National Laboratories (LANL) puts out lots of different bioinformatics tools with their more well known tools, from my perspective, being PhaME (bioRxiv paper), EDGE (NAR paper) and GOTTCHA (NAR paper). 

I was a part of a group from WRAIR that tested their EDGE platform when it was originally being developed. While it has a lot of good software integrations (packaging up of open source software for pathogen detection, surveillance and other analyses), for me, 'black box' bioinformatics solutions always have their caveats. I see these 'all-in-one' answers as exploratory tools that require validation at the very least with other pipelines. Additionally, with the large software packages like EDGE, if there is no comprehensive manual or links to manuals of programs integrated into the system then I am suspicious of the 'default' settings and why they were set in that way. I've have had many a reviewer ask for justifications on my data analysis set ups and if you cannot justify your settings (default or not) then you don't understand what the analysis is really doing to your data. Perhaps I just have an innate distrust of machine default outputs.

To LANL and the EDGE team's credit this is posted on their readthedocs site for EDGE:

"While the design of EDGE was intentionally done to be as simple as possible for the user, there is still no single ‘tool’ or algorithm that fits all use-cases in the bioinformatics field. Our intent is to provide a detailed panoramic view of your sample from various analytical standpoints, but users are encouraged to have some insight into how each tool or workflow functions, and how the results should best be interpreted." 

Like they read my mind...this is good advice for any tool(s) that you use.

MICROBE 2018 recap - Bioinformatics - Microbial Genomes Atlas (MiGA)

So I don't typically tweet during meetings because it's hard enough to listen and take notes without attempting to be witty and post on twitter accurately at the same time, it's just not one of my gifts. My twitter account in general comes and goes much like this blog with my postings limited to what I find interesting in the field or what I am learning in the field. So - like this blog, my twitter goes dark here and there and lights up when I'm inspired to share. I'm impressed I have as many followers as I do - thank you faithful followers!

BUT, for this talk I found this amusing enough given we were in a bioinformatics software talk that we saw this...

@ASMicrobiology #ASMicrobe at the new #Bioinformatics Tools and Discovery session... While loading the talk on MiGA we get an "out of memory" error. The humor is not lost on me. pic.twitter.com/eJQ1xBDHcb

— Mel Melendrez (@UseqMiseq) June 8, 2018

"Out of Memory" is what that says. So I was amused for sure.

So I have my moments of within meeting tweeting.

During this talk we were updated on the Microbial Genomes Atlas (MiGA).

MICROBE 2018 recap - Bioinformatics - Comparison of Metaproteomics Tools

So Dr. Pratik Jagtap is from my current stomping grounds...Minnesota. He's a research assistant professor at the University of Minnesota, Minnesota Supercomputing Institute (MSI). His work focuses on tool development for proteomic analysis specifically for Galaxy-P and he has an impressive array of publications in the field. His latest 2018 offering:

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework

Stalking his twitter account it is chock full of great links to studies and research being conducted in the are of proteomics so if that's a field of interest to you I recommend you follow his account.

In this particular presentation he was investigating the latest metaproteomic software offerings and evaluating their performance with an oral microbiome set courtesy of Rudney and colleagues 2015. He wasn't specific as to which Rudney 2015 article but I'm guessing it's this one - which appears to have links to fastq datasets from an oral microcosm study. Or it could be this publication from 2015 which Rudney is on, but not first or last author which talks about an oral microbiome dataset used specifically for Galaxy P, though I cannot be sure because the article is paywalled.

Comparison studies in bioinformatics are always informative because it sets down metrics by which we can start using to interrogate these programs and evaluate which ones are best for our experimental design, which are potentially flawed, what are the pros and cons for each such that we can justify their use or exclusion in our studies.

MICROBE 2018 recap - Bioinformatics - Machine Learning and Microbial Ecology

I confess...if 'machine learning' is in the title I am immediately crawling into my hole of computational fear at the impending deluge of terminology I will most likely have to google 90% of.

I was pleasantly surprised with Demetrius' presentation - so kudos on describing how machine learning is applied to microbial ecology and making it palatable for those of us unversed in machine learning.

Demetrius DiMucci: Boston University

A machine learning approach for predictive and 

explanatory microbial ecology

I really liked how Demetrius started off, my imperfect quote, more of a paraphrase below:

"Pretend you are a community ecologist - who has isolated your community and sequenced everything that is there. With thousands of organisms you want to learn what's causing the function of this community... a typical approach is 'reductionist' meaning you isolate using media (culturing). This is quite impractical for 1000's of organisms, so what do we do? We cheat!"

Always a great way to grab attention... Let's Cheat!

MICROBE 2018 recap - Bioinformatics - Gi-Scanner

So half, if not more, of my life is dedicated to using (and breaking) bioinformatic software, so of course, when I heard there was a whole poster talk session on new bioinformatic tools I grabbed my computer staked out a sweet spot where I could charge everything up and waited for the black-box buttons to be pushed...

Dr. Sophie Shaw (right) and I

Before I jump in...a shout out to my lovely fellow bioinformatician who I haven't seen in 4 years (we met at the Workshop for Genomics in 2014) yet prolifically follow on twitter and instagram. We found eat other at Daniel McDonald's poster presentation for the American Gut Project...awww Dr. McDonald bringing together globally floating around bioinformaticians since 2018.

Alright - back to the session: First up -

YoungJae Hur, Seoul National University: 

Gi-Scanner: An algorithm to predict genomic islands by 

comparative genomics

So, the first thing I typically do when someone touts a new piece of software is google/google scholar it. I want to find the software page...github, sourceforge, lab webpage - I like going to the source, looking at documentation and making my own assessments. Alas for Gi-Scanner it is not published or available on a website yet. I was a bit confused in the presentation as to whether we were looking at a piece of software to identify genomic islands OR if we are waiting on a database of genomic islands for V. cholerae identified by their software but that their software may not actually be available for public use. I want to think the former - that the software will be readily available soon and that the database will also be published/available for those interested in particular with V. cholerae.