Author: Johanna Ohm

New skills learned at VectorBite’s training workshop

Posted on by Johanna Ohm

Blog post by Rebecca Brown

This year’s VectorBiTE meeting was held at the Asilomar conference centre by the stunning bays of Monterey, California. In the days ahead of the working group sessions, post-doc and graduate students attended a three-day training workshop on quantitative tools for vector-borne diseases. Led by the charismatic Leah Johnson (Virginia Tech) and Samraat Pawar (Imperial College London), the workshop took the format of lectures followed by guided examples of analysis to gain practical experience, with assistance from instructors Fadoua El Moustaid (Virginia Tech), Marta Shocket (Stanford University) and Matt Watts (Imperial College London).

The training started off with data wrangling and an introduction to the R packages dyplr and tidyr, showing off their aesthetically pleasing summaries! The importance of minimizing editing your raw data file was highlighted (something I am guilty of) thus a key outcome was to record all steps used to process your data with an R script. We learned that models are not only useful to explain relationships in observed data, but models are key for revealing underlying mechanisms driving observed patterns. In the context of vector-borne diseases this is critical for predicting disease outbreaks or assessing the efficacy or suitability of interventions. Model fitting by least squares methods was taught and we worked through an example of fitting a non-linear least squared model to insect trait data. This was followed by teaching on the likelihood based methods: Maximum likelihood estimation and Bayesian analysis, which was new territory for me. We were taken through the steps to fit a model using maximum likelihood by creating a function to return the negative log likelihood to build the likelihood profile based on the data.

Participants of the 2018 VectorBiTE training workshop pose in front of the conference center.

On the final day, our new-learned skills were put to the test with a challenge! Our group tackled understanding mosquito development rate variation with temperature by maximum likelihood estimation. All groups came together at the end to share how they addressed their problem. The previous two days of intensive training paid off because there was a notable improvement in my understanding and ease of using the new techniques. I’m looking forward to applying these tools in my own analysis now. Thank-you VectorBiTE!

———-

Rebecca Brown is a PhD student at the Institute of Biodiversity, Animal Health and Comparative Medicine in Glasgow. She is interested in the impact of land-use change on the transmission of vector-borne diseases. Her current research is on the behaviour and ecology of Anopheles vectors of Plasmodium knowlesi malaria in Malaysian Borneo.

VectorBITE 2018: Meeting Recap

Posted on by Johanna Ohm

The VectorBite 2018 meeting just wrapped up a productive week of training and working group meetings at the Asilomar Conference Center near Monterey, CA. This year’s meeting was split into two parts: a three-day training session for post-docs and graduate students followed by two days of working group meetings.

The training covered an introduction to data management, visualization, and fitting models to data and then focused on specific topics in using data on vectors to fit trait data to mechanistic and statistical models and to fit population dynamics models to data taken from Vectorbyte‘s VecDyn database. The training materials are posted on GitHub.

The working group meetings started off with brief presentations from working group leaders to discuss plans and give an overview of the working group’s interests. Thursday and Friday were then spent hashing out ideas and in some cases, outlining papers to write or experiments to do with group members.

Working group topics included modeling how life history trade-offs in vector traits may impact transmission of vector-borne disease, creating a framework to understand how behavioral manipulation of vectors may similarly impact transmission, characterizing when and where rate summation breaks down for predicting thermal performance curves for different vector traits, discussion of tick questing behavior, whether we can use body size or other traits to create integral projection models for vector populations, and individual-based models for vector populations.

Two days go by fast, especially when we only get to meet once per year! The discussions were stimulating, groups outlined concrete goals and plans for how to complete tasks between now and next year, and we still made time for some walks or runs along the beach and drinks at the Asilomar pub. Here’s to another great #Vbite meeting!

 

New methods to detect infected mosquitoes

Posted on by Johanna Ohm

Blog post by Jo Ohm

The past year has seen a number of clever new methods to detect infection in mosquito vectors. These new methods which allow for improved detection and monitoring of the time course of infections inside mosquitoes will be powerful tools for exploring many questions central to the research of VectorBiters.  If inventions fuel science and science fuels invention, the future of vector-borne disease research has exciting findings to come from the use of these new tools. Below are some of the latest methods published in the literature which promise to improve our understanding of vector-borne disease transmission:

  1. Detection of virus in mosquitoes using Near Infrared Spectroscopy (NIRS) – NIRS has already been demonstrated to be useful in ageing mosquitoes and identifying between Anopheles species and a recent paper in Science Advances suggests it can be used to detect Zika-infected mosquitoes. Pluses: 18x faster and 110x cheaper than using RT-qPCR for Zika detection ; Minuses: destructive sampling, requires highly sensitive microspectrometer, unknown if it will work with field samples
  2. Malaria sporozoites measured through sugar feeding – A Nature Scientific Reports paper published earlier this month reports a nondestructive way to detect when malaria-infected mosquitoes become infectious by using PCR to detect parasites left behind in sugar-soaked cotton or FTA cards. This method is similar to methods already developed to detect dengue from mosquito sugar water. Pluses: Nondestructive sample, possible to use on individual mosquitoes (?) ; Minuses: Feeding on sugar through FTA cards reduces survival compared to feeding on sugar through cotton
  3. Identifying Aedes species and Wolbachia-infection status with a cellphone – Recently on bioRxiv, Bhadra et al report detection of Wolbachia-infected mosquitoes using an assay that fluoresces in response to the presence of Wolbachia-specific nucleic acids, which should be useful for surveillance purposes following Wolbachia-based mosquito field releases. Pluses: No DNA extractions required, likely to work in field settings ; Minuses: ?
  4. Track mosquitoes using rhodamine b – Mosquito mark-recapture experiments are notoriously difficult and marking with fluorescent dies can have fitness costs on the mosquitoes being marked. A new way to mark mosquitoes using rhodamine b fed through a honey solution was reported to have no detectable fitness costs on marked males. This should be a useful tool for capturing dispersal distance, mating patterns, and age of wild mosquito populations. Pluses: No fitness costs for marking mosquitoes for a mark-recapture experiment and the dye transfers to females through the seminal fluids of marked males ; Minuses: Only demonstrated in males so far, probably works for females (?)

New and exciting technologies have been developed to improve our approach to detecting and monitoring infectious mosquitoes. What other methods are out there? What methods don’t exist yet that would improve our understanding of vectors and vector-borne disease? Have any VectorBiters tried any of these methods yet?

Update from the “FutureBites” Working Group: What traits determine host and parasite range in bird malaria?

Posted on by Johanna Ohm

Blog post by Jenny Dunn

Pathogens infect a wide range of hosts: some are complete specialists, while others infect a diversity of species. Vector-borne diseases also range in the breadth of hosts that are involved in transmission cycles, but little is known about the traits that determine these host ranges. The VectorBite working group, FutureBites, has a subgroup focused on bird malaria. As  are using the avian malaria system, which has unrivaled diversity among parasites infecting vertebrates (~600 mitochondrial cytochrome b lineages of Plasmodium currently described), to identify host and pathogen traits associated with specialism and generalism in both pathogens and hosts.

Progress during the 2017 meeting at Imperial

Over the course of the meeting we spent time developing key questions to address, cleaning databases, and identifying methods to use in downstream analysis.

A main outcome for the meeting was discussing and deciding on three main objectives for the first set of analyses:

  1. Identify patterns of host-parasite-vector specificity through creation of matrices of malaria lineage/host specificity and malaria lineage/vector specificity
  2. Identify traits associated with specialist/generalist parasites, where specialism/generalism is defined either as host richness per se, or as phylogenetic host relatedness
  3. Identify traits associated with specialist/generalist host, where specialism/generalism is defined either as malaria parasite richness per se, or as phylogenetic parasite relatedness

To answer these questions we found and curated several datasets. These include two publicly available databases: MalAvi (which has data on malaria-bird host pairwise associations and malaria-vector pairwise associations) and avian host trait data (http://www.esapubs.org/archive/ecol/E088/096/metadata.htm). Bird host cell characteristics (curated by CF) and vector-host pairwise associations (curated by JD) were curated for this analysis. Phylogenies for bird and malaria species were constructed using maximum likelihood methods from sequence data publicly available.

We identified multiple possible definition of specialism and generalism, and defined both terms for our analyses. With AP’s expertise, we began analysing associations and writing code for further analyses.

Progress following the 2017 meeting

We are making steady progress despite time limitations, and have met over Skype since Imperial. We have been developing our thoughts around what further analyses might be possible with the datasets that already exist, and outlining the datasets along with their limitations before finalizing the analyses we want to address.

Future plans

We plan to continue and complete the analyses described above as time allows, and begin to draft a manuscript (led by CF and JD) for submission in 2018.

We plan to extend these analyses by using similar methods to examine vector-host and vector-parasite pairwise associations and associated traits, once vector trait data are available through the VecTrait database.

 

Group members: Jenny Dunn, Christina Faust, Andrew Park, Ana Rivero, Richard Hall, Sylvain Gandon

VectorBase’s PopBio site is populated with data

Posted on by Johanna Ohm

VectorBase, a database of vector genomic, population-level, and phenotypic data, sponsored by the National Institute for Allergy and Infectious Diseases Bioinformatics Center, has recently added new mosquito surveillance data for cities around the U.S.

For VectorBite members looking for freely available data on mosquito population abundance and occurrence, the website has maps of where mosquito traps have been placed for surveillance purposes and the abundance and species identity of mosquitoes found in those locations. The newly added data come from Las Vegas, Nevada, and several counties in Florida, including Manatee, Hernando, Orange, and South Walton. For some counties, surveillance data covers the past 9 years. This adds to the two years of data from Iowa that were already in the “PopBio” database.

The VectorBase website is a rich resource for anyone looking for mosquito surveillance data. Check out the newly updated data!

Bloodfed Mosquito Meals Make Spiders Sexy

Posted on by Johanna Ohm

Blog post written by Marta Shocket.

Last month my friend and lab mate Meghan Howard gave a talk at a global health conference and got one of those questions: a question not directly related to her research, but fundamental, big, and interesting. The kind of question that you might hear from a civilian (non-scientist) friend or a relative around the Thanksgiving table.

The question was: How important are mosquitoes for ecosystems? What, if any, calamities would befall the Earth if we could somehow engineer their disappearance? Meghan was quick on her feet and gave a great answer (1). However, our whole lab was having the same nervous reaction in the audience: we knew it was a question that she hadn’t prepared for, and none of us were quite sure how we would answer it in her place. Discussing her improvised answer over lunch, we decided that at our next open lab meeting we would split into teams and tackle popular topics in vector biology. That way, the next time one of us was in the hot seat, we’d be more prepared.

Even though the question about the ecological importance of mosquitoes caught me off guard, it wasn’t a new question for me. I’d been interested enough to bookmark some popular science articles on that exact topic—but of course, not enough to actually read them.

Since others in the vector ecology community might be in a similar boat, this entry will be the first of three blog posts covering the topics we researched for our lab meeting: the role of mosquitoes in ecosystem functioning, Wolbachia bioengineering, and other types of vector bioengineering. Each post will have a short summary of the topic, links to popular and scientific articles if you want to dig deeper, and hopefully some fun and unexpected facts (including the one behind this post’s click-bait title).

So, how important are mosquitoes? The general consensus among scientists is that with a few exceptions, mosquitoes are not very important for ecosystem functioning. Many animals eat mosquitoes, but they only comprise a significant proportion of biomass in the arctic tundra. The migratory birds that breed there would definitely miss them as a food source if they disappeared (2,3). Little Forest Bats in Australia also depend mostly on adult mosquitoes for food (3), and larval mosquitoes are a critical food source for mosquitofish. Beyond these three examples, most other predators are probably generalist enough that they could subsist on other prey items (2).

Aside from being eaten (and of course, transmitting pathogens), mosquitoes have a couple other minor roles. Many mosquito species eat nectar, and some plants rely on them for pollination (2,3). Larval mosquitoes are important for structuring the communities of protists that live inside pitcher plants, and for recycling nutrients to make them available to the plants (2).

However, the most sensational use for mosquitoes was one I found in a relatively obscure article reviewing the potential use of spiders as biocontrol (4). They referenced a study showing that Evarcha culicivora, an East African jumping spider, specifically targets blood-fed Anopheles mosquitoes over sugar-fed ones. The reason for this preference: eating blood-fed mosquitoes gives both males and females a scent that makes them more sexually attractive to mates (5). Not exactly earth-shattering in terms of ecosystem services, but it definitely makes a salacious blog title, and could spice up next year’s conversation around the Thanksgiving table.

A caveat to end: magically disappearing all mosquitoes is an interesting thought-experiment, but not very realistic. The biotech strategies being developed to drive down mosquito populations all target single species that spread infections to humans. These villains account for a tiny proportion of the 3,500 described species of mosquitoes, so the mosquitofish and pitcher plants don’t need to worry too much.

Sources:

(1) You can watch her talk about mosquito communities across a land use gradient in Costa Rica on youtube <https://www.youtube.com/watch?v=38xcapLLB7s>. The question in question occurs at around 12:22.

(2) https://www.nature.com/news/2010/100721/full/466432a.html

(3) https://theconversation.com/why-dont-we-wipe-mosquitoes-off-the-face-of-the-earth-54005

(4) http://www.dipterajournal.com/pdf/2018/vol5issue1/PartA/4-6-15-487.pdf

(5) Jackson RR, Cross FR. Mosquito-terminator spiders and the meaning of predatory specialization. Journal of Arachnology. 2015; 43:123-142. PDF

 

Marta Schocket is a post-doc in the Mordecai lab at Stanford University and a member of VectorBite.

New manuscript out by the EIP working group

Posted on by Johanna Ohm

At the last VectorBiTE meeting at Imperial College, the EIP working group sketched out a plan for a review paper on how to define and improve measurements of the extrinsic incubation period (EIP) for malaria parasites. Our review is finally complete and has been published in Parasites & Vectors. The article is available here.

Don’t have time to read the manuscript? Here are a few of the key points we made in the paper:

(1) Malaria’s EIP has been inconsistently measured and reported in the past. Many studies report EIP as the time until the first observation of sporozoites in the salivary glands following an infectious feed. However, this ignores variation in development time that is likely present in a mosquito population and may not be representative of the EIP we want to capture in models of transmission if this earliest time of development is not the time when infectious mosquitoes are also feeding. See our Figure 1 for variation in EIP documented from the literature compared to the Detinova model that is used to predict EIPs based on temperature.

(2) Many factors are likely to affect EIP but most studies only consider temperature. The classic model to predict malaria’s EIP (the Detinova model) uses mean temperature to predict EIP. We evaluated evidence from the literature that fluctuating temperatures, parasite genetics, vector genetics, and other environmental factors such as mosquito diet, may also impact EIP.

(3) The best way to report EIP may be using the median EIP value observed from a mosquito population, rather than the time until first observed sporozoites. We run through an example of how using EIP estimated as the time until first observation vs estimated as the median EIP changes predictions of a proxy for potential transmission intensity (the number of alive and infectious mosquitoes). Future studies that make use of non-destructive sampling techniques to look at sporozoites in the salivary glands of individuals over time will hopefully make studies on EIP easier to do and better capture variation in EIP between individual mosquitoes.

Patterns of mosquito biting rates: data from the field

Posted on by Johanna Ohm

Blog post written by Philipp Boersch-Supan and  Cat Lippi from University of Florida.

VectorBiTE scientists from the QDEC Lab Group at the University of Florida have now published a study on seasonal and daily patterns in human biting rates of mosquito taxa capable of malaria transmission in Southern Ecuador. In collaboration with SUNY Upstate Medical University and the Ecuadorian Ministry of Health, the data for this study were collected during a massive effort to eradicate local transmission of malaria in Ecuador’s Southern coast during the 2000’s, resulting in successfully eliminating autochthonous transmission in this region. Although no transmission of malaria has been detected in Ecuador’s southern coast since 2011, mosquito-borne diseases such as malaria, dengue, and other viruses remain a major threat to people’s livelihoods throughout Latin American, which makes it crucial to prevent reestablishment of these diseases where local infection has been eliminated.

Surveillance is key to assessing and maintaining elimination status. Because it is extremely difficult to directly monitor mosquito populations and the pathogens carried by them, vector-borne diseases are often monitored through case numbers of human infections. This adds an additional layer of uncertainty: Infections may be asymptomatic, and access to health care is unevenly distributed, leading to reporting biases. Furthermore, once local elimination is achieved, relying on human case reports means reestablishment can only be detected after transmissions and infections have occurred, leaving limited options for preventative vector control measures. It is therefore important to not only monitor infections themselves, but also the potential for mosquito-borne transmission, or the risk of infectious bites on humans. This risk is often quantified by observing human bite rates or human landing rates. While these do not directly measure infections, they are often cited as a proxy for species presence, density of blood-seeking females, and thus the capacity for disease transmission.

Collecting data on human biting rate in the field poses an ethical dilemma, as field technicians are exposed to the risk of disease transmission. Bite rates in this study were estimated from human landing catch (HLC), where technicians equipped with stockings collected mosquitoes with an aspirator as they landed. These counts were taken hourly both inside and outside of residential buildings across five localities. Because not all mosquito taxa occur at all times and at all study sites, such datasets often exhibit a large proportion of zeros, i.e. observational periods where the observer was not bitten at all by one or more taxa.  Elsewhere the observer may sit near a site that is favourable for mosquito breeding and experience many bites in an observational period. Such data are challenging to model with traditional statistical models, because the surplus zeroes, as well as the occasional large counts are not captured by commonly used probability distributions, lead to biased estimates of mean biting rates.

Ecologically the observed quantity (realized bites) arises from a two part process; mosquitoes must be present and able to bite for there to be any bites to count.

We therefore used a two part statistical model to analyze the data, a so-called hurdle model. Hurdle models specify one process to model the probability or odds for zero counts and another process for the positive bite count or rate. The idea is that positive counts occur once a threshold – the hurdle – is crossed. If the hurdle is not cleared, then we have a count of zero.

The models allowed us to determine whether biting activity was fundamentally different for different taxa, and to identify temporal and spatial factors (being inside or outside a residential structure) influencing bite rate. We were interested in these potential differences because vector competence (i.e. the ability to transmit malaria) differs among mosquito taxa. We found that biting rates varied significantly among species and time. Anopheles albimanus was the species most commonly observed biting. The occurrence of An. albimanus bites in a given hour was four times as likely as no bites, with an average of 4.7 bites per hour. All taxa exhibited exophagic feeding behavior, meaning that outdoor locations increased both the odds and incidence of bites across taxa.

Being outdoors more than doubled the odds of being bitten by An. albimanus and increased the number of bites per hour by about 50%. Differences between indoor and outdoor locations were less pronounced for the two other taxa, both concerning the odds of receiving any bites and the number of bites received. Months of peak high and low biting activity varied for the three taxa; the highest and lowest respective months for significant biting activity were March and July for An. albimanus, July and August for An. punctimacula, and February and July for Culex spp.

Because vector competence is not the same across all mosquito taxa, our results have important implications for vector control. Aggregating bite rates or other measures of mosquito activity across taxa potentially obscures species-specific peaks of activity. Vector control efforts that are based on aggregated counts may therefore not effectively target the most competent vectors at their peak activity, and by the same token, epidemiological models based on aggregated activity measures may be less accurate in predicting disease outbreaks. Furthermore, the differences observed in biting activity across taxa indicate a need for accurate species descriptions in regions with multiple vectors, as taxonomic confusion between closely related mosquitoes may obscure patterns in transmission risk. While the collection of species-specific bite rate data requires more observer effort, the information provided by the surveillance and analysis methods in our study can be incorporated to allow more targeted, household-level vector control programs, thus providing a powerful tool in controlling and preventing  the reemergence of pathogens.

Update from the Species Interactions in Transmission Group (SpIT!): RCN Year 2

Posted on by Johanna Ohm

Blog post by Catherine Herzog

Excitement was in the air this past summer as members of the SpIT group gathered in London for the second RCN meeting and had a chance to finally see each other again in person since the first RCN in March 2016.  Five new members joined the group: Richard Hall (UGA), Michelle Evans (UGA), David Vasquez (UGA), Trishna Desnai (Denison), and Marie Russell (EPA Fellow, Imperial).

In its first year, SpIT! began by investigating how predation influences vector traits relevant to vector-borne disease (VBD) transmission.   We developed a mathematical model of predation and vectorborne disease risk. While looking to parameterize the model, we began a subgroup focused on literature searches and meta-analysis of the predation literature on our four vectors of interest: the mosquito, tick, aphid, and triatomine.  We explored the following questions:

  1. What evidence is there that vector populations of any stage are regulated by predators? In which life history and vector traits?
  2. What are the direct and indirect effects of predators on vector traits and transmission? What are the consumptive and non-consumptive effects?
  3. Are predator effects mediated by: predator/parasitoid/parasite identity, vector identity, type of experiment (natural/experimental), natural/ introduced predator, location/latitude, landscape, life stage, predator strategies?

At this second RCN meeting, the SpIT group continued working on our predation model, literature review and meta-analysis, and had whiteboard discussions about two other vector interactions: co-infection and competition.

After considering all three species interactions (predation, co-infection, and competition) all together, we rephrased our original question to: Do species interactions (co-infection, interspecific competition, or predation) impact vectorborne disease transmission and under what conditions?  In this second year of the RCN, SpIT plans to complete the already started predation model and meta-analysis work and proceed to move forward with a manuscript aiming to look at the mechanisms of species interactions that impact vectorborne disease transmission.  In this process, we will also identify and record gaps in knowledge, design future experiments for Simple Measurements Across Sites and Habitats (SMASH) work. Ultimately, this work will contribute to improved applications for potential control of VBD.

The RCN meeting was not all work, work, work and our members had time to enjoy the hike and BBQ food truck organized by the RCN Board, to chat at the pub down the street at the end of the day, and to enjoy the new swag stickers of the SpIT logo, developed by Trishna Desnai.  The SpIT group had a productive and fun time at the 2017 RCN and is already looking forward to the 2018 RCN.

Some recent buzz in Public Data Access

Posted on by Johanna Ohm

Blogpost by Sam Rund

In September, the Editor-in-Chief of JGR: Oceans, Peter Brewer, wrote a provocatively titled blog post, “Do You Expect Me to Just Give Away My Data?,” in which he stated:

“When you publish a research paper, you are also simultaneously publishing the data that supports your work. The readers of your article have equal rights to see both the words and the numbers – they are inseparable.”

Brewer then went on to ask:

“But what constitutes “data”? What about the raw instrument readings? What about the calibration runs? What about all the model code? etc, etc.”

As vector biologists, we are in a very different field (Brewer is an ocean chemist), but his question is still a good one for us to ponder. It is also exactly the kind of question that the VectorBite working group, VectorBite Open-access vector science: Data acquisition and use, is working on addressing. Indeed, our minimal standards document begins to address this question for our field: who collected the data, when was it collected, how was it collected, what is it (taxonomy), how was it identified, etc. Look for a draft coming soon!

Closer to our field, in October, Maryam Zaringhalam currently an AAAS Science & Technology Policy Fellow at the National Library of Medicine, published a Blog Post titled, “Scooped! A very personal case for open science” where she reports the tale of how she was ‘scooped,’ on a project looking for the RNA modification pseudouridine sites, “. . . or, to be more precise, the first four times I got scooped —all in the span of one month.”

Dr. Zaringhalam went on to explain that while this was devastating (she was a graduate student at the time), it was an excellent example of one benefit of Public Data Access.  She took the four published reports, retrieved the archived data, performed new reanalysis, and found of the 450 sites listed between the four works – only two overlapped.

“I offered technical and biological explanations for the variability, but the fact remained that these techniques, published in high-impact journals, would likely result in false leads and dead ends in the quest to understand the biological role of pseudouridine.”

Zaringhalam’s story highlights the utility of having results replicated across labs and the need for open access data as a scientific “double-check” to confirm findings and allow other researchers to re-analyze.

With October 23-29 designated as Open Access Week, it seems fitting to open the discussion on open access in the VectotBite community. Comment on the post with your experiences using open access data for vector research or learn more at http://openaccessweek.org and at figshare’s “State of Open Data Report”.

On the vector front, VectorBiTE’s Ecoinformatics Data Platform is now online. You can also check out a large dataset of state of Iowa mosquito surveillance records now online here.