Opisthorchiasis caused by O. viverrini (Opisthorchis viverrini; Ov) infection is a significant public health issue in many Southeast Asian countries, including Thailand, Lao PDR, Vietnam, and Cambodia, infecting more than 12 million people (Kaewpitoon et al., 2008; Sripa et al., 2021). The liver fluke infection is caused by eating raw or uncooked fish products, which is common in Thailand’s northeastern and northern regions, particularly in rural areas. Infection progression can result in cholangitis, obstructive jaundice, hepatomegaly, cholecystitis, cholelithiasis, and cholangiocarcinoma (CCA), among other hepatic disorders (Sripa et al., 2007). Biliary damage caused by O. viverrini examined in the hamster model showed that the parasite infection can solely cause CCA in the long term (Songserm et al., 2009). Hence, O. viverrini and C. sinensis liver fluke parasites have been classified as “Group 1” biological carcinogens (World Health Organization, 1994).

Upon ingesting raw infected fish, O. viverrini metacercariae excyst in the duodenum. The newly excysted juveniles (NEJs) start to migrate towards the ampulla of Vater, relying on chemotaxis and glycogen reserves for the movement (Tielens et al., 1982). Once within the bile duct, they mature into self-fertilizing adult flukes in the bile ducts, thereby acquiring the reproductive capabilities necessary to release eggs (Harinasuta and Harinasuta, 1984; Orido, 1990). The pathogenic mechanisms of O. viverrini-induced CCA (Ov-CCA) involve parasite-feeding-triggered inflammation, host-helminth interactions at the tegument interface, and immunopathology driven by secreted ES (Excretory Secretory products) products and EVs (Extracellular Vesicles) effector repertoire (Chaiyadet et al., 2019; Glaser, Gaudio et al., 2009; Sripa, 2003; Sripa et al., 2012).

Understanding parasite biology and host interactions better is imperative to identify new drug targets or potential vaccine candidates. The analysis of genomic (Laha et al., 2007; Young et al., 2014), transcriptomic (Jex et al., 2012), and proteomic (Mulvenna et al., 2010) data of O. viverrini has provided us with a deeper understanding of Ov-tegument and secreted proteins. These proteins may function both protectively and as immunogens in host-specific interactions. Despite substantial research efforts and omics advancement, no vaccine conferring efficacious protection against trematode infections has achieved the level of effectiveness required for commercial deployment (McManus, 2020). Furthermore, the lack of interest from pharmaceutical industries and attention from health agencies and policies is related to the fact that no vaccine against opisthorchiasis is available for clinical use. This can also be attributed partially to the abundance of proteomics data and findings, yet relatively less focus on filtering and analysing these datas for wet lab and translational investigations. Hence, incorporating immunoproteomics is essential in this context, as it facilitates a filter in the rigorous validation of potential markers, thereby bridging the gap between discovery and clinical verification (Pedersen et al., 2005; Ejazi et al., 2018). Moreover, previous investigations exploring antibody responses in the context of parasitic infections have demonstrated the value and feasibility of such immunoproteomics-based studies (Jedlina-Panasiuk, 2002; Pleasance et al., 2011; Zhang et al., 2015; Driguez et al., 2016).

Antigens identified through immunoproteomics analysis spanning from the tegument to ES molecules and EVs of O. viverrini can be computationally evaluated. Furthermore, assessing vaccine solubility, antigenicity, immunogenicity, and allergenicity predictions informs the selection of epitopes optimally suited to activating robust host defences (Kapuganti et al., 2022). For the last few years, advanced Artificial intelligence (AI) and Machine Learning (ML) algorithms to predict protein structures and modelling have permitted structural prediction with about 90% accuracy in silico (Stevens and He, 2022). Moreover, molecular docking simulations yield insights into projected binding dynamics between prioritised epitopes and immune receptors (Sahoo et al., 2022; Che et al., 2023). Access to these two web-based servers alone holds immense potential to significantly streamline academic research efforts and lead to substantial cost savings. We believe it is now imperative to incorporate immunoinformatics in the prioritisation process before in vitro and in vivo studies, thereby propelling the progression toward clinical trials more efficiently (Figure 1). Hence, this review highlights the initial phases in vaccine design, which involves the integration of immunoproteomics utilising omics data and computational bioinformatics tools for the systematic studies on helminthic parasites. This integration has the potential to identify numerous protein marker candidates suitable for clinical investigations and to advance the rational design of multi-epitope vaccines against opisthorchiasis.

The multi-omics journey for O. viverrini started over 15 years ago by generating and analysing so-called expressed sequence tags (EST) that profiled the first description of gene discovery for the liver fluke O. viverrini (Laha et al., 2007). Since 2010, the integration of multi-omics strategies and methodologies, including liquid chromatography-mass spectrometry (LC-MS), next-generation sequencing, and various -omics based technologies, has significantly enhanced our understanding of trematode biology-spanning across the field of genomics, transcriptomics, proteomics, metabolomics, and glycomics (Table 1) (Mulvenna et al., 2010; Jex et al., 2012; Talabnin et al., 2013; Young et al., 2014; Prasopdee et al., 2019; Kokova et al., 2020). Therefore, research efforts focused on the genomes, transcriptomes, and proteomes of O. viverrini isolates at a global level hold great potential to significantly advance our understanding of the molecular pathogenesis of O. viverrini associated CCA. Such investigations are expected to lay the groundwork for identifying critical targets for designing new interventions.

As -omics techniques enable the broad discovery of temporally-resolved molecular alterations underlying host-parasite interactions, disease progression, and therapeutic targets during different stages of parasite infection (Hasin et al., 2017; Mitreva, 2022). Considerable progress in parasitology has been made through generating and interrogating omics data (Gardinassi et al., 2018; Liu et al., 2021; Athieniti and Spyrou, 2023). The term “immunoproteomics” is becoming a mature field with potential impact on developing immunoproteomics-based assays and vaccines (Fulton and Walker, 2013). Immunoproteomics explicitly profiles the host immune recognition of protein antigens, aiding the isolation of immunoreactive proteins and leveraging such data to predict and prioritise optimal vaccine candidates efficiently (Dennehy and McClean, 2012).

Immunocapture of antigenic proteins followed by mass spectrometry has proven an effective strategy for learning vaccine targets from trematode parasites (Bennett and Robinson, 2021). The assays have played a crucial role in identifying antigenic proteins from parasitic organisms, including parasitic trematodes (Reamtong, 2013). They leverage an expanding array of technologies to identify and quantify antigenic peptides and proteins that induce immunity (Hayes et al., 2018).

The immunoproteomics techniques include a wide range of gel-based, array-based, mass spectrometry, DNA-based, and in silico methodologies to gain unprecedented insights into disease aetiology and progression and facilitate the identification of novel vaccine candidates and biomarker discovery (Table 3). By comprehensively profiling the host immune response at the protein (antigen) level, immunoproteomics enhances our understanding of pathogenic mechanisms and enables accelerated selection of optimal antigens for rational vaccine design against complex infectious diseases. Therefore, integrating immunoproteomics strategies with omics-related discoveries provides a powerful approach for unravelling the functions of upregulated proteins during the infection and a successful vaccine design.

With the plethora of knowledge in the Omics domain, immunoinformatics, combining immunology and bioinformatics, offers innovative solutions in drug design and identifying vaccine candidates (María et al., 2017; Tomar, 2020). Variations in proteins released in the form of EVs (Trelis et al., 2022) and ES proteins (Wang et al., 2013; Yeshi et al., 2022), and tegument surface proteins may help O. viverrini maintain stability, survival, and immune evasion strategies. This can be explored in the systematic vaccine design (Figure 3). Hence, whole proteome analysis in trematode parasitism is beneficial for identifying crucial parasite proteins associated with virulence, exploring essential protein interactions, and uncovering distinctive immuno-modulatory mechanisms contributing to prolonged infection (van der Ree and Mutapi, 2015). Moreover, longitudinal profiling of antibody responses through immunoproteomic tools reveals antigenic proteins expressed in specific parasite developmental stages, from NEJ to immature and adult developmental phases.

The strategy for developing a vaccine against cancer-inducing O. viverrini parasites involves using epitopes from antigens to elicit an immune response. However, the primary challenge in creating a cancer vaccine lies in understanding the immunology of infection and identifying inflammation-inducing antigens that can potentially help parasites in vital functions. These challenges can be addressed by blending omics and immunoproteomics results with immunoinformatics (Figure 4).

The in silico screening and experimental validation process streamlines identifying and evaluating potential antigens from a liver fluke parasite, offering a faster and more efficient alternative to traditional methods. Candidate antigens can be evaluated in silico for population coverage (Bui et al., 2006), antigenicity (Doytchinova and Flower, 2007), physicochemical properties (Wilkins et al., 1999), and ability to induce B- and T-cell epitopes (Bui et al., 2006; Khan et al., 2022). Particularly intriguing are fluke-specific antigens predicted to stimulate both humoral and cellular immune responses in infected hosts, reflecting scientific inclination and necessity. Structural modelling and prediction of immunogenic epitopes using servers like AlphaFold2 (Jumper et al., 2021; Yang, et al., 2023) allows rigorous in vitro testing through molecular docking and dynamics to generate hypotheses regarding immune receptors, proteins and designed vaccine interaction (Soleymani et al., 2022). Recombinant protein expression techniques such as cloning predicted multi-epitope subsequences into prokaryotic vectors like pET28b (+) provide a robust means of antigen production and evaluation in immunogenicity studies. (Martinelli, 2022). Various computational and bioinformatics tools and techniques are available in immunoinformatics, particularly in the context of vaccine development (Table 4), which can be utilized for parasitic and infectious diseases.

The synergistic application of experimental vaccine design using omics and computational immunoinformatics represents a promising approach to develop safe, efficacious multi-antigen helminth vaccines rationally. This integrated framework may help overcome decades of challenges by accelerating the selection of optimized antigens that induce robust, broad, and long-lasting immunity against diverse helminth strains. Such vaccines targeting multiple parasite stages and species could significantly reduce the health burden of soil-transmitted helminthiases and other NTDs that predominantly impact low-resource populations worldwide.

Vaccination has played a pivotal role in mitigating the spread of numerous pathogens and is a cornerstone in disease eradication efforts (Rauch et al., 2018). However, despite its proven efficacy, a notable absence of licensed anti-helminth vaccines for human use remains. Furthermore, helminths, being eukaryotic organisms, present many challenges for vaccination strategies due to their distinct biological characteristics. Hence, immunoinformatics and reverse vaccinology offer transformative avenues in vaccine development. These methodologies leverage computational tools and genomic insights to streamline the identification of potential vaccine candidates from the pool of identified proteins.

Researchers use helminth genomes and proteomes to identify antigenic proteins that initiate immune responses, aiding in the development of customized vaccines. Immunoinformatics methods then prioritize vaccine candidates based on their capacity to elicit protective immune responses, reducing the risk of vaccine failure during advanced clinical trials. Immunoinformatic analysis has been conducted across diverse parasite species. For the focus of our review, we present a curated selection of studies employing the vaccine development pipeline specifically within the domain of helminth parasites, as illustrated in (Table 5). This implies ongoing progress in helminth vaccine research through continual discovery and prioritization of novel candidates.

The lack of attention, prioritization and funding of helminth infections within health organisations and research spheres can be attributed to the absence of opisthorchiasis vaccines currently available for clinical use. Recent strides in transcriptomics, genomics, and proteomics have shed light on the potential engagement of genes and proteins during the early stages of O. viverrini, influencing aspects such as survival, motility, immune evasion, and pathogenicity. However, to obtain a clear view of antigen targets, it is crucial to integrate data across various “omics” modalities (Vahabi and Michailidis, 2022), and immunoinformatics represents a sensitive high-throughput platform for profiling immunogenic antigens from the parasite. Insilico analysis with high predictive outcomes can limit the use of animal models, leading to more sustainable research (Pappalardo et al., 2019). In the future, there is hope that in silico trials can replace human trials (Ebert et al., 2021). Furthermore, in silico analyses in the O. viverrini vaccine design process can significantly reduce costs and expedition timelines. Computational screening of antigen candidates can yield substantial savings by minimising experimental wet-lab validation and animal trials, thereby mitigating financial barriers for this under-resourced yet high-impact disease (Saldanha et al., 2023). This approach expedites the entry of numerous vaccine candidates into clinical trials, often ahead of schedule (Shawan et al., 2023). However, the vaccine design against carcinogenic parasites like O. viverrini must carefully account for the inflammation associated with its infection and the potential presence of undiagnosed tumours in endemic populations. This consideration is vital due to the intricate interplay between tumours and immune cells, whereby various pathways influence each other, ultimately steering toward distinct outcomes (Gonzalez et al., 2018; Bedognetti et al., 2019). Multistage vaccines have been proposed as an effective strategy in complicated pathogens, as this may show a synergistic effect and would be particularly desirable for biliary tissue-dwelling pathogenic flukes (Maizels, 2021). Furthermore, the choice of proper and safe synthetic immunomodulatory adjuvants should be carefully selected/designed (Zhao et al., 2023) and follow-up in vivo studies. Overall, combining immunoproteomics and immunoinformatics offers a compelling strategy to accelerate the rational design and development of vaccines, holding significant potential for preventing and controlling infectious diseases in forthcoming years.

The current period marks an exciting phase for research in this field, with significant advancements seen in recent years, particularly in the structure-based design of new antigens, antibodies, and binders. Traditional vaccine development faces significant challenges, including high costs, hesitancy, stringent safety requirements, and societal demands for perfect efficacy. Additionally, issues like immunosenescence, limited adjuvants, and concurrent health problems in the developing world complicate efforts. Therefore, the global availability of in silico technologies in vaccine design and access to tools utilising supercomputers via internet-enabled interfaces maximises their utilization across diverse research communities internationally. In NTDs based research, merging AI and ML with biological, medical, and biochemistry-based approaches holds immense promise for driving breakthroughs. This convergence is poised to accelerate the discovery of novel biologics, offering new avenues for combating such neglected diseases effectively (Rodrigues and Ersching, 2014; Winkler, 2021). This initiative aims to end the neglect and contribute to achieving the Sustainable Development Goals (World Health Organization, 2020).

While converging experimental and computational vaccine design holds promise for rational helminth vaccine development, certain limitations must also be acknowledged. These in silico based tools require high-quality input data to train algorithms and predict outcomes accurately. Further experimental validation is advised to refine helminth vaccine formulations before proceeding to clinical testing. Moreover, ensuring vaccine effectiveness and safety profiles suitable for use in endemic areas where NTDs are prevalent and infrastructure is limited poses difficulties. In summary, while integrating immunoproteomics and immunoinformatics holds promise for optimising vaccine design, transitioning from theoretical constructs to practical, field-ready vaccines for helminth diseases remains a formidable long-term challenge. Overcoming both natural and technical barriers necessitates sustained dedication from all stakeholders involved.