Category Archives: Antibodies

AIRR Community Meeting VI May 17-19 

Eve, Brennan and I were delighted to attend the sixth AIRR (adaptive immune receptor repertoire) Community Meeting: Exploring New Frontiers in San Diego. Eve and I had been awaiting this meeting for a mere 3 years, since it was announced during the last in-person AIRR Community Meeting back in 2019. Fortunately, San Diego did not disappoint. 

After a rocky start (featuring many hours stuck in traffic on the M40, one missed flight and one delayed flight), we made it to California! The three day conference had ~230 participants (remote and in-person) and featured great talks from academia and industry. We particularly enjoyed keynote talks from Dennis Burton on rational vaccine design using broadly neutralising antibodies, Gunilla Karlsson Hedestam on functional consequences of allelic variation, Shane Crotty on covid and HIV vaccine design, and Atul Butte on uses of electronic health record data and how we should all found start-ups.

We had fun delivering a tutorial on OPIG antibody tools and, most importantly, we all won AIRR t-shirts in the raffle (potentially we were the only people who noticed how to enter on the conference app). Highlights outside of the conference included paddle boarding and seeing hummingbirds, pelicans, sealions, seals, ‘Garibaldi’ the state fish, and meeting Bob the golden retriever at a surfing shop. We’re now off to find jobs on the West Coast so we can live at the beach….

 The AIRR community has many webinars and talks available on their youtube channel https://www.youtube.com/c/AIRRCommunity

Sarah, Eve & Brennan

Antibodies as Drugs: Keystone Symposia

Between the 27th April and 1st of May, I was very fortunate to be able attend the Antibodies as Drugs Keystone Symposium and give my first conference talk internationally, in which I spoke about the methods our group has developed for using structure to make predictions about where an antibody binds relative to other antibodies. This included paratyping [1], Ab-Ligity [2] and most recently SPACE [3].

I will preface this by saying that lots of the work people spoke about was unpublished, which was so exciting, but makes for a difficult blog post to write. To avoid any possibility of putting my foot in my mouth I will keep the science very surface level. The conference was held at the Keystone resort in Colorado, and the science combined with a kind of landscape I have never experienced before made for an extremely cool experience. This meeting was originally combined with a protein design meeting, and the two were split by COVID – this meant that in-silico methods were the minority in the program, but I didn’t mind that as the computational work that was presented was quite diverse so it was definitely a good representation of the field still. I also really enjoyed the large number of infectious disease talks in which we got a good range of the major human pathogens – ebolaviruses, SARS-CoV-2 of course, dengue, hantaviruses, metapneumovirus, HIV, TB and malaria all featured. The bispecific session was another highlight for me. The conference was very well organised and I liked how we were all asked to share a fun fact about ourselves – one speaker shared that he is a Christmas tree farmer in his spare time (I won’t share his name in case he is keeping that under wraps). That made me reconsider how fun I can truly consider myself…

Without turning this into a travel blog, I also want to add that Keystone was insanely beautiful and make you look at some pics I got. 

We got to experience snow
Continue reading →

Benford’s law and OAS

Benford’s law is an observation that in numerical data (produced by many kinds of process), the leading digit tends to be small. Wikipedia tells you that it in datasets obeying Benford’s law, the number 1 appears as the leading digit about 30% of the time while 9 appears less than 5% of the time (p(n) = log10(1+1/n) where n is the leading digit). Wikipedia further lists multiple kinds of data where this tends to be true such as electricity bills, population numbers and physical and mathematical constants, and particularly where data can be described by a power law.

Power laws and antibodies have been co-discussed in reference to network descriptions of antigen-experienced BCR repertoires [1], which are often described as scale-free to use the network terminology (following a power law). This means a few highly-connected nodes in the network and lots of nodes with few or no connections. This is an obvious candidate for Benford’s law.

This is of no practical relevance, but I wondered if I could see Benford’s law in other kinds of data besides clone counts in the Observed Antibody Space (OAS). For example, I looked at the leading digit in the number of sequences in all of the data units in OAS. It looks like a good fit for Benford’s law (though with more density at the smaller leading digits) and has a chi-squared value of 0.007 (Figure 1A).

Continue reading →

CryoEM is now the dominant technique for solving antibody structures

Last year, the Structural Antibody Database (SAbDab) listed a record-breaking 894 new antibody structures, driven in no small part by the continued efforts of the researchers to understand SARS-CoV-2.

Fig. 1: The aggregate growth in antibody structure data (all methods) over time. Taken from http://opig.stats.ox.ac.uk/webapps/newsabdab/sabdab/stats/ on 25th May 2022.

In this blog post I wanted to highlight the major driving force behind this curve – the huge increase in cryo electron microscopy (cryoEM) data – and the implications of this for the field of structure-based antibody informatics.

Continue reading →

What is a plantibody?

Plants can be genetically engineered to express non-native proteins, for example, crops can be engineered to produce insect toxins in order to improve disease-resistance. However, I was not aware of their ability to express antibodies until, inspired by my expanding collection of house plants, I googled ‘plant immune systems’. 

Plants don’t naturally produce antibodies – they do not possess an adaptive immune system or any circulating immune defence cells. Despite this, plants can be made to express and assemble full length antibody heavy chains and light chains. This was first published back in 1989, when Hiatt et al. [1] successfully introduced mouse immunoglobulin genes to tobacco plants and produced functional antibodies with reasonable efficiency. The excellent term ‘plantibody‘ was coined soon after, to refer to antibodies and fragments of antibodies produced by plants transformed with antibody-coding genes. 

Continue reading →