Analytics for Investigation of Disease Outbreaks: Web-Based Analytics Facilitating Situational Awareness in Unfolding Disease Outbreaks.

BACKGROUND: Information from historical infectious disease outbreaks provides real-world data about outbreaks and their impacts on affected populations. These data can be used to develop a picture of an unfolding outbreak in its early stages, when incoming information is sparse and isolated, to identify effective control measures and guide their implementation. OBJECTIVE: This study aimed to develop a publicly accessible Web-based visual analytic called Analytics for the Investigation of Disease Outbreaks (AIDO) that uses historical disease outbreak information for decision support and situational awareness of an unfolding outbreak. METHODS: We developed an algorithm to allow the matching of unfolding outbreak data to a representative library of historical outbreaks. This process provides epidemiological clues that facilitate a user's understanding of an unfolding outbreak and facilitates informed decisions about mitigation actions. Disease-specific properties to build a complete picture of the unfolding event were identified through a data-driven approach. A method of analogs approach was used to develop a short-term forecasting feature in the analytic. The 4 major steps involved in developing this tool were (1) collection of historic outbreak data and preparation of the representative library, (2) development of AIDO algorithms, (3) development of user interface and associated visuals, and (4) verification and validation. RESULTS: The tool currently includes representative historical outbreaks for 39 infectious diseases with over 600 diverse outbreaks. We identified 27 different properties categorized into 3 broad domains (population, location, and disease) that were used to evaluate outbreaks across all diseases for their effect on case count and duration of an outbreak. Statistical analyses revealed disease-specific properties from this set that were included in the disease-specific similarity algorithm. Although there were some similarities across diseases, we found that statistically important properties tend to vary, even between similar diseases. This may be because of our emphasis on including diverse representative outbreak presentations in our libraries. AIDO algorithm evaluations (similarity algorithm and short-term forecasting) were conducted using 4 case studies and we have shown details for the Q fever outbreak in Bilbao, Spain (2014), using data from the early stages of the outbreak. Using data from only the initial 2 weeks, AIDO identified historical outbreaks that were very similar in terms of their epidemiological picture (case count, duration, source of exposure, and urban setting). The short-term forecasting algorithm accurately predicted case count and duration for the unfolding outbreak. CONCLUSIONS: AIDO is a decision support tool that facilitates increased situational awareness during an unfolding outbreak and enables informed decisions on mitigation strategies. AIDO analytics are available to epidemiologists across the globe with access to internet, at no cost. In this study, we presented a new approach to applying historical outbreak data to provide actionable information during the early stages of an unfolding infectious disease outbreak.

Selection of phage-displayed accessible recombinant targeted antibodies (SPARTA): methodology and applications.

We developed a potentially novel and robust antibody discovery methodology, termed selection of phage-displayed accessible recombinant targeted antibodies (SPARTA). This combines an in vitro screening step of a naive human antibody library against known tumor targets, with in vivo selections based on tumor-homing capabilities of a preenriched antibody pool. This unique approach overcomes several rate-limiting challenges to generate human antibodies amenable to rapid translation into medical applications. As a proof of concept, we evaluated SPARTA on 2 well-established tumor cell surface targets, EphA5 and GRP78. We evaluated antibodies that showed tumor-targeting selectivity as a representative panel of antibody-drug conjugates (ADCs) and were highly efficacious. Our results validate a discovery platform to identify and validate monoclonal antibodies with favorable tumor-targeting attributes. This approach may also extend to other diseases with known cell surface targets and affected tissues easily isolated for in vivo selection.

Large scale production of phage antibody libraries using a bioreactor.

One of the limitations of the use of phage antibody libraries in high throughput selections is the production of sufficient phage antibody library at the appropriate quality. Here, we successfully adapt a bioreactor-based protocol for the production of phage peptide libraries to the production of phage antibody libraries. The titers obtained in the stirred-tank bioreactor are 4 to 5 times higher than in a standard shake flask procedure, and the quality of the phage antibody library produced is indistinguishable to that produced using standard procedures as assessed by Western blotting and functional selections. Availability of this protocol will facilitate the use of phage antibody libraries in high-throughput scale selections.

Specific binder for Lightning-Link® biotinylated proteins from an antibody phage library.

Many applications required protein biotinylation. We routinely use biotinylated proteins to select single chain antibodies from phage and/or yeast display libraries. During phage selection the biotinylated antigens are bound to streptavidin coupled magnetic beads, while during yeast display, the biotinylated antigens are used during flow cytometry for both analysis and sorting. The Lightning-Link® Biotin kit, a rapid straightforward biotinylation kit that avoids the need for dialysis, is particularly useful when the amount of available protein is limiting. During routine screening of antibody libraries we identified a specific clone that bound a universal neo-epitope generated only when antigens are biotinylated with the commercial Lightning-Link® kit, with an affinity of ~10nM. Non-biotinylated proteins, and those biotinylated using alternative methods - the Thermo Fisher commercial kit or in vivo biotinylation using the Avitag (Ashraf et al., 2004) - were not recognized by this antibody. Using deep sequence analysis, the specific antibody was identified as being the most abundant in a number of different selections. This indicates the need for caution when using such modifying reagents, because of the possibility of selecting antibodies against the modification, rather than the target protein, and also highlights the value of deep sequencing analysis during display based selections. Furthermore, this antibody may have great utility in the analysis of proteins biotinylated using this method.

Using phage and yeast display to select hundreds of monoclonal antibodies: application to antigen 85, a tuberculosis biomarker.

BACKGROUND: Current diagnostic methods for tuberculosis (TB), a major global health challenge that kills nearly two million people annually, are time-consuming and inadequate. During infection a number of bacterial molecules that play a role in the infective process are released and have been proposed as biomarkers for early TB diagnosis. Antigen 85 (Ag85) is the most abundant secreted TB protein, and a potential target for this diagnostic approach. One of the bottlenecks in the direct detection of such bacterial targets is the availability of robust, sensitive, specific antibodies. METHODS: Using Ag85 as a model, we describe a method to select antibodies against any potential target using a novel combination of phage and yeast display that exploits the advantage of each approach. RESULTS: The efficiency of this approach was attested to by the 111 specific antibodies identified in initial screens. These were assessed for binding to the different Ag85 subunits, affinity, and activity in sandwich assays. CONCLUSIONS: The novelty of this approach lies in the possibility of screening the entire output of a phage antibody selection in a single experiment by yeast display. This can be considered analogous to carrying out a million ELISAs. The monoclonal antibodies (mAbs) identified in this way show high binding affinity and selectivity for the antigens and offer an advantage over traditional mAbs produced by relatively expensive and time consuming techniques. This approach has wide applicability, and the affinity of selected antibodies can be significantly improved, if required.