Delayed-Type hypersensitivity to latex: Computational prediction of MHC class II epitopes on latex allergens

This article was rejected by several journals. Hence I feel the concept is fundamentally wrong. I have posted the full article here. The referee comment from the last journal is also included.

• The object of the study is laudable. However, the data presented here is too preliminary for publication.
• Class II MHC molecules bind short peptides of 12 to 20 residues long. The concept of MHC binding to whole antigen is grossly not acceptable as given in Table 1.
• Moreover, studies of this nature require experimental verification for publication.
• It is strongly advised to look at MHCBN, MHCPEP and SYFPETHI for the type of peptides MHC molecules bind.
• The design of the study should be narrowed down to a single antigen with overlapping peptides to multiple class 2 alleles for a reasonable argument.

Key words
Natural Rubber Latex, MHC Class II.

Abstract
Delayed type hypersensitivity to natural rubber latex is rare compared to IgE mediated immediate reactions. Binding of allergens to MHC Class II is a crucial step in the presentation of antigens to CD4+ T Cells responsible for delayed reactions. Computational prediction of MHC class II epitopes on thirteen known latex allergens using SMM-align method revealed strong binding with several alleles. This shows that latex allergens are capable of initiating delayed type hypersensitivity in susceptible individuals.

Background
Natural rubber latex (NRL) derived from the rubber tree (Hevea brasiliensis) is an important allergen causing mostly IgE mediated immediate reactions like urticaria, angioedema and asthma. [1] The existence of a true NRL induced delayed type hypersensitivity (type IV) is still debated. Delayed type hypersensitivity reactions are attributed to additives like thiurams and carbamates. [2] The coexistence of the type I and type IV patterns and entities like protein contact dermatitis [3] further complicate the issue. However incidence of true type IV hypersensitivities ranging from 1.2 to 6% has been reported following the introduction of an NRL containing patch test series. [4]

During the sensitization phase of contact hypersensitivity, epidermal Langerhans cells internalise the allergen, migrate to the regional lymph node and present the processed allergen bound to MHC Class II molecules to CD4 T cells. MHC Class II binding site consists of a groove open at both ends and several pockets binding peptides with 13 to 25 residues. [5] MHC molecules exhibit high degree of genetic variation which enables them to bind variety of peptides.

As IgE from latex-sensitive patients bind to several proteins, there is still no consensus on which latex proteins are antigenic. However information on thirteen officially accepted latex allergens designated serially from Hev b 1 to 13 is available from the online repository www.allergen.org and are summarized in Table 1. [6,[7]

We tried to computationally predict the MHC class II epitopes on these antigens using SMM-align method. SMM-align is a novel stabilization matrix alignment method based on scoring matrices that evaluate the contribution to binding of different residues in a peptide. [8] T cells are likely to recognize MHC binding peptides and initiate a cellular response. [9]

Methodology
The protein sequences of all thirteen allergens were downloaded from www.allergen.org and were added to a single file. This file was used for MHC Class II epitope prediction with the publicly available SMM-align server using default parameters. The server returns IC50 prediction scores (concentration of competing ligand which displaces 50% of the specific ligand) covering fourteen HLA DR alleles for each nanomer within the query peptide. Allergens with at least one nanomer with IC50 value less than fifty were considered as binders.

Results
Strong binding to one or more alleles was shown by all allergens except Hev b 5. Hev b 2 was the most promiscuous allergen binding several alleles. DRB1*0101 was the most commonly bound allele. Results are summarized in Table 1.

Discussion
NRL is an allergen causing mostly IgE mediated immediate type hypersensitivity. Though there have been significant advances in molecular biology of latex allergens, their ability to initiate delayed-type hypersensitivity has been subject to debate. Computational prediction of MHC class II binding regions on latex allergens adds credence to reports of type IV contact hypersensitivity to NRL. [4]

Prediction of MHC binding peptides is a commonly employed step in the identification of T cell epitopes. [9] MHC epitope related data is available from several databases like SYFPEITHI, [10] MHCBN [11] and IEDB [12]. Several algorithms like ARB [13] and SMM-align [8] are available for prediction of MHC class II binding peptides. Algorithms for scanning promiscuous peptides that can bind multiple MHC class II molecules are also available. [14] Promiscuous peptides are important for vaccine development and immunotherapy. [5] In our study Hev b 2 bound to six out of fourteen tested HLA DR alleles.

Conclusion
Most of the characterized latex allergens contain segments which can strongly bind MHC class II alleles and are capable of initiating delayed type hypersensitivity without a hapten in susceptible individuals. Certain promiscuous allergens like Hev b 2 bind to several MHC alleles making them ideal candidates for immunotherapy. [15] However computational prediction of MHC binding has limited accuracy and clinical validation is essential.

References

1 Reunala T et al.,. Latex allergy and skin. Curr Opin Allergy Clin Immunol 4: 397-401 (2004) [PMID: 15349039]
2 Miri S et al.,. Prevalence of type I allergy to natural rubber latex and type IV allergy to latex and rubber additives in operating room staff with glove-related symptoms. Allergy Asthma Proc 28: 557-63 (2007) [PMID: 18034975]
3 Doutre MS. Occupational contact urticaria and protein contact dermatitis. Eur J Dermatol 15: 419-24 (2005) [PMID: 16280292]
4 Sommer S et al.,. Type IV hypersensitivity reactions to natural rubber latex: results of a multicentre study. Br J Dermatol 146: 114-7 (2002) [PMID: 11841376]
5 Wang P et al.,. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol 4: e1000048 (2008) [PMID: 18389056]
6 Breiteneder H et al.,. Molecular and immunological characteristics of latex allergens. Int Arch Allergy Immunol 116: 83-92 (1998) [PMID: 9652300]
7 Wagner S et al.,. Hevea brasiliensis latex allergens: current panel and clinical relevance. Int Arch Allergy Immunol 136: 90-7 (2005) [PMID: 15627782]
8 Nielsen M et al.,. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinformatics 8: 238 (2007) [PMID: 17608956]
9 Sette A et al.,. The relationship between class I binding affinity and immunogenicity of potential cytotoxic T cell epitopes. J Immunol 153: 5586-92 (1994) [PMID: 7527444]
10 Schuler MM et al.,. SYFPEITHI: database for searching and T-cell epitope prediction. Methods Mol Biol 409: 75-93 (2007) [PMID: 18449993]
11 Bhasin M et al.,. MHCBN: a comprehensive database of MHC binding and non-binding peptides. Bioinformatics 19: 665-6 (2003) [PMID: 12651731]
12 Peters B et al.,. The immune epitope database and analysis resource: from vision to blueprint. PLoS Biol 3: e91 (2005) [PMID: 15760272]
13 Bui HH et al.,. Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications. Immunogenetics 57: 304-14 (2005) [PMID: 15868141]
14 Zhang GL et al.,. MULTIPRED: a computational system for prediction of promiscuous HLA binding peptides. Nucleic Acids Res 33: W172-9 (2005) [PMID: 15980449]
15 Tabar AI et al.,. Specific immunotherapy with standardized latex extract versus placebo in latex-allergic patients. Int Arch Allergy Immunol 141: 369-76 (2006) [PMID: 16943675]

Protein-Protein Docking Problem.

I am looking for a solution to the following problem. Any insight will be greatly appreciated.

A membrane receptor (A) has an extracellular domain (AE), transmembrane domain (AT) and intracellular domain (AI).

A bacteria (B) binds to (AE) leading to dimerization of (A) at (AT) and subsequent downstream signaling through (AI).

(A) has no known natural ligands.

(A) has one known inhibitor (I) binding to (AE)

The structure of (AE) bound to (I) is available from PDB.

How do we identify which protein in (B) binds to (AE).

The obvious solution is to dock all proteins with known structures in (B) to all known pockets in AE. Any better solutions?

The art of taking online help:

I am not a big time researcher with lots of international experience. However I would like to make an attempt to suggest few guidelines for the young Indian bioinformatician, seeking online help for project or showcasing their profile online.

How to address a researcher online? Generally in research community, people are not bothered much about show of respect. Hence sir, respected sir, the most adorable etc can be translated to lack of confidence or to too much submissiveness. Hence it is appropriate to address anybody by the second name adding the appropriate title. Just using the first name is also OK. However title is often taken seriously and addressing a Dr/Prof as Mr is a cardinal sin even if you add a liberal dose of sir/almighty to that.

Career guidance is often done face to face or over the phone or through forums specifically dedicated for that. However before posting career guidance questions to forums search the forum for similar questions unless your profile is unique. Questions like I am going to finish my Kinder Garden What should I do next to become a successful bioinformatician is unlikely to fetch many answers. If you dont have enough time to search the forum, dont expect anybody else to send a personal two page letter to you.

The same applies to very broad, open ended questions. Questions like How is bioinformatics important for clinical medicine? is unlikely to get much attention. Be as specific as possible. Do not expect others to provide complete answers in a platter. Answers will be mostly very short, incomplete and often cryptic (because you may not know what the other person is talking about). Be ready to do some background research on the answer rather than asking for more information.

Posting your profile in online forums is also an art. Bioinformatics is a very broad field and employers look for certain specific skills which you may not always have. I often see sequence analysis, genomics, proteiomics, computer programming, PERL, RUBY, EMERALD, systems biology, drug designing, structural and molecular biology, talking, reading and sleeping in the skill set, everyone competing to make the complete list. In reality, no body can be a complete bioinformatician and it is better to showcase your core competency which needs to be substantiated by your projects or publications.

Please post your comments / criticisms / suggestions here.

Bioinformatics Projects

I feel bioinformatics projects broadly fall into three categories.

1. Academic project as part of UG or PG course.
2. Professional projects for biotech/drug companies
3. Hobbyist/personal projects
   

When you do an academic project it is important to achieve a preset target within a limited time frame. Hence you have to adopt a bottom up approach wherein you know what your final result is going to be and work your way up. It is always better to keep it simple. You always have time to do more complicated things later on.

Professional projects also have a predefined goal. However it has a wider scope but often has the backing of a team. Funding is also available. This is what most of us aspire to do once we become full fledged professionals.

The third type of projects is for people who are not primarily bioinformaticians, but try to explore this nascent specialty, keeping their field as the initial entry point. They often try a top down approach and may not be always successful!

Let me suggest the following topics, categorized based on your area of expertise.

• IT Prepare a database (organism, disease, or any other) and deploy it online
  
• Microbiology Select an organism and do a comparative genomic study
  
• Biochemistry Model a pathway using systems biology tools and discuss its clinical significance.
  
• Pharmacology Docking studies and study of the targets of existing drugs.
  
• Clinicians Expression profile study of any disease of interest.
  
• Vet / Agri Functional genomic study of any chosen gene.

Counting conditional Occurrences using Prolog.

Counting conditional occurrences using Prolog.

I wanted to implement the following rule in prolog for my IISA project.

If the percentage of coil region is greater than 20% the homologue detection algorithms may become unreliable. The coil module of IISA returns prolog database in the following format.

coil(105,a,0.000).
coil(109,g,0.001).
coil(110,l,0.004).
coil(111,l,0.014).
coil(112,v,0.055).
coil(113,g,0.055).
coil(114,s,0.371).
coil(115,e,0.416).
coil(116,k,0.860).
coil(117,v,0.955).
coil(118,t,0.998).
coil(119,m,0.999).
coil(120,q,0.999).
coil(121,n,0.999).

ie coil(position, aminoacid, probability of being part of coil).

I wanted to count the number of facts with the probability exceeding a cutoff value, say 0.7.

Though it is simple problem, I could not find any solution for this even after googling for few hours. Finally I found this code on the net.

%Code to count the number of proofs for a goal. Found on the net.
count_proof(Goal, N) :-
            flag(counter, Outer, 0),
            (   call(Goal),
                flag(counter, Inner, Inner+1),
                fail;
                flag(counter, Count, Outer),
                N = Count
            ).
Though it worked well (I have still not figured out how!) the code is SWI-Prolog specific and did not work in JLog prolog applet I use for IISA web interface.

Finally I learned about findall and bagof
But still it took some time to figure out how to use findall for my purpose because the description read findall (Var, Database, Array) and to use length(Array). Using coil (_,_,A) as database will count only the number of aminoacids and I didn’t know how to implement the condition A>0.7.
Finally somewhere I found the actual definition for findall (Var, Goal, Array) which solved my problem, though I wasted a whole day on this simple problem.

Here is the final code.

%The region is coil if the value is greater than threshold
coil_region(Cutoff, Val):-
                     coil(_,_,Val),
                     Val>Cutoff.
                    
coil_percent(Region, Total, Percent):-
                     setting(coil,X),
                     findall(Val,coil_region(X,Val),R),
                     length(R,Region),
                     findall(C,coil(_,_,C),A),
                     length(A,Total),
                     Total>0,        %Avoid division by zero
                     Percent is (Region/Total) * 100,!.

coil_percent(0,0,0).

IISA Home Page.

Zostavax

Merck recently gained approval for a vaccine called Zostavax for preventing herpes zoster reactivation in elderly people. This live virus vaccine is unusual in that it is to prevent reemergence, not to prevent initial infection. Can the same concept be used for recurrent herpes simplex infection which is much more disabling than herpes zoster in younger people?

Vigyaan CD Part II [NX SERVER]

Running NX server & accessing it from windows machines.

To start NX server, click on KNOPPIX -> Services ->NX server.

The script is supposed to add a new user called nxuser. However this functionality is not working properly in Vigyaan 1.0. Hence you have to use the root account or the default knoppix account. But by default both these accounts do not have passwords. Hence you have to set a password for both these accounts.

Click on the terminal icon on status bar.
su
passwd
<change the password>
Close the terminal window
System ->kduser
Select knoppix
Uncheck Disable account’
Click Set password and set a new password.

Now on your windows machine download and install nx client from NOMACHINE.

Find the local IP of the vigyaan box by typing ifconfig in a terminal window. Now you can access vigyaan box from your windows machine.