Open access peer-reviewed chapter
Abstract
The field of intestinal parasite diagnosis has experienced significant advancements in recent years, propelled by technological innovations and the pursuit of more precise and effective diagnostic methods. A notable development in this area is the widespread adoption of molecular diagnostic techniques, such as polymerase chain reaction and loop-mediated isothermal amplification. These cutting-edge methods provide improved sensitivity and specificity compared to traditional microscopy-based approaches, enabling the detection of intestinal parasites even at low concentrations and in complex clinical samples. Additionally, the creation of multiplex polymerase chain reaction assays allows for the simultaneous identification of multiple parasite species in a single test, streamlining the diagnostic process and reducing turnaround time. Furthermore, the integration of artificial intelligence and machine learning algorithms into diagnostic platforms shows great potential for enhancing the accuracy and efficiency of parasite detection. In conclusion, these recent advancements present unparalleled opportunities to enhance the precision, speed, and accessibility of parasite diagnosis, ultimately leading to better patient outcomes and more effective public health interventions in endemic regions.
Keywords
- parasites
- intestinal
- diagnosis
- microscopy
- molecular techniques
- new developments
1. Introduction
Intestinal parasites continue to present significant health risks on a global scale, particularly in regions where sanitation and hygiene practices are lacking. These parasites, varying in pathogenicity, remain prevalent and continue to cause illness and discomfort in both animals and humans. Despite the advancements made by the pharmaceutical industry in developing treatments for parasitic infections, these infections persist and impose a substantial burden of disease in many parts of the world.
For instance, as indicated by the recent Pan-European Economic Assessment, the economic impact of helminth infections in ruminants is estimated to be comparable to or greater than that of animal diseases, amounting to an estimated €941 million annually [1]. The repercussions of neglected parasitic diseases on human populations, particularly children in low-resource settings, are profound [2]. Furthermore, zoonotic parasites have the ability to move between different hosts, compounding the disease burden for individuals who come into contact with contaminated food, water, soil, or vectors [3, 4].
Parasites, though minuscule and imperceptible to the naked eye, can be observed under a microscope. The community of parasites that pose a threat to human health includes protozoa, helminths, and ectoparasites. It is estimated that 357 million cases of morbidity, predominantly caused by protozoa such as Cryptosporidium, Entamoeba, and Giardia, resulted in 33,900 deaths and the loss of 2.94 million disability-adjusted life years annually [5] Furthermore, over 1.4 billion individuals are afflicted with helminth infections [6]. In addition to their impact on human health, parasites also play a role in causing diseases in plants and other organisms. Notable examples include Giardia, which is transmitted through contaminated water, toxoplasmosis, which is spread by cats, and malaria which is spread by mosquitos [7]. Globally, one species of helminth parasite alone infects over 800 million people [8]. The prevalence and impact of parasitic infections underscore the importance of continued research and intervention efforts to mitigate their detrimental effects on public health.
In developing regions such as East Asia, South America, and Saharan Africa, there exists a plethora of over 100 species of human intestinal parasites that collectively produce an astonishing 200,000 eggs daily. Alarmingly, an estimated 41,500 human fatalities are reported annually as a direct result of parasitic infections [9]. The manifestations of these infections vary widely, encompassing clinical presentations that range from malnutrition to asymptomatic anemia, and in some cases, even leading to the development of cancer [10, 11]. Despite advancements in diagnostic techniques, conventional light microscopic examination continues to serve as the gold standard method for the detection and diagnosis of several parasitic diseases, notably malaria [12].
Timely and accurate diagnosis is paramount for the effective management and control of parasitic infections. Throughout the years, a multitude of diagnostic techniques have been developed and refined to improve sensitivity, specificity, and efficiency. Understanding the composition of parasite communities and their impact on disease risk is crucial for any surveillance program aimed at reducing the parasite burden. Equally important is the utilization of cutting-edge diagnostic tools to optimize resource allocation for parasite control.
For many years, parasitologists have predominantly relied on traditional diagnostic methods involving microscopic examination. Conventional light microscopy remains the preferred method for diagnosing certain parasitic diseases, such as malaria [12]. While these techniques are cost-effective and straightforward, they are often plagued by issues of reproducibility and lack the necessary specificity and sensitivity. Moreover, microscopic methods are labor-intensive and necessitate skilled personnel for accurate interpretation.
As we transition toward a future centered around molecular tools, the reliance on traditional diagnostic techniques may pose challenges [13]. The shortage of trained professionals proficient in identifying parasites through conventional means underscores the importance of embracing advancements in diagnostic technology. By staying abreast of the latest tools and methodologies, we can enhance our ability to combat parasitic infections effectively. In this chapter, we will be exploring the latest advancements in the diagnosis of intestinal parasites. Prior to delving into these new developments, it is imperative to provide a brief overview of the traditional diagnostic methods that have been utilized in the past.
2. Conventional methods
Traditional diagnostic methods for identifying intestinal parasites primarily rely on microscopic analysis of stool samples. These methods include direct smear microscopy, formalin-ether concentration technique, Kato-Katz thick smear technique, and Fecal Floatation Technique. These techniques allow for the visualization of parasite eggs, larvae, or cysts under a microscope, aiding in the detection of various parasitic infections. In addition to these conventional methods, Fecal Immunoassays, specifically enzyme-linked immunosorbent assays (ELISA), are also utilized for diagnosing intestinal parasites. These tests target specific antigens or antibodies produced by parasites in the stool sample, making them particularly effective in identifying certain protozoan infections such as Giardia and Cryptosporidium. Overall, these diagnostic approaches play a crucial role in accurately identifying and treating intestinal parasitic infections, ultimately contributing to improved patient outcomes.
While cost-effective, these methods have limitations in terms of sensitivity, particularly for low-intensity infections, and they may necessitate skilled personnel for accurate interpretation. There are also additional numerous shortcomings associated with these methods, including variable sensitivity, resource, and time consumption, all of which have the potential to significantly impact the results of clinical examinations.
Additionally, the traditional clinical parasitology classification and detection process faces challenges in maintaining staff competency and engagement. The clinical parasitology laboratory is further hindered by the fact that educated technologists are increasingly drawn to technology-driven and automated disciplines within the laboratory, leaving a shortage of adequately trained personnel to manage the traditional methods effectively [14]. Results obtained through the diagnosis of parasites are often reliant on clinical signs and symptoms, which are susceptible to human error. This can result in higher mortality rates, unnecessary drug purchases, and economic burdens [15]. Consequently, there is a pressing need for alternative methods that can provide more accurate and reliable diagnosis results.
3. Point-of-care testing (POCT) devices
Point-of-care testing (POCT) devices are sophisticated medical diagnostic tools engineered to swiftly and conveniently provide diagnostic results directly at the patient’s point of care, whether it be in a clinic, doctor’s office, or out in the field. These devices are typically compact, user-friendly, and have the ability to produce precise results with minimal sample processing. The advent of POCT devices for diagnosing intestinal parasites has revolutionized decentralized testing and enhanced access to diagnostic services, particularly in areas with limited resources. These portable and intuitive devices employ a variety of detection methods, such as immunochromatographic assays, nucleic acid amplification, and digital microscopy. Examples include rapid diagnostic tests (RDTs) for identifying specific parasite antigens in stool samples and smartphone-based microscopy systems equipped with advanced image analysis algorithms for automated parasite detection.
Some drawbacks of point-of-care testing (POCT) devices include the potential for user error, limited test menu options, and the need for proper training and quality control measures. User error can occur if healthcare providers are not adequately trained on how to use the devices, leading to inaccurate results. Additionally, POCT devices may have a limited test menu, which could restrict the types of tests that can be performed at the point of care. Finally, maintaining quality control measures and ensuring the accuracy of results can be challenging with POCT devices, requiring ongoing monitoring and oversight.
4. Molecular techniques
The introduction of nucleic acid-based detection methods has the potential to not only enhance the accuracy of diagnosis but also improve the efficiency and impartiality of intestinal parasite diagnosis. This is particularly significant given the opportunity to integrate complementary assays into highly automated platforms. Through the refinement of diagnostics, there is a likelihood of better assigning effective antiparasitic treatments, a critical consideration in light of the escalating cases of drug resistance.
In recent years, molecular diagnostic techniques have transformed the field of parasitology by enabling swift and precise detection of parasites. PCR, first described in 1985, is a groundbreaking technique that allows for the in vitro amplification of a specific DNA fragment through a cyclic process involving denaturation, primer hybridization, and DNA strand elongation using a thermostable DNA polymerase [16, 17]. Polymerase chain reaction (PCR)-based assays, such as conventional PCR, real-time PCR, and multiplex PCR, offer exceptional sensitivity and specificity in identifying a broad spectrum of intestinal parasites. These advanced techniques enable the detection of parasite DNA even at minimal concentrations, facilitating early diagnosis and treatment [16, 17]. Following the initial publications on DNA amplification by PCR, it was foreseen that this innovative technology would revolutionize molecular parasitology and the diagnosis of parasitic infections [18, 19]. Prior to this breakthrough, the use of specific DNA probes in research and diagnostics was hindered by the limited sensitivity of direct hybridization assays without amplification. The advent of PCR offered a solution by enabling the specific amplification of minute DNA quantities. In 1995, a comprehensive review by J.B. Weiss highlighted the abundance of research papers on DNA-based methods for detecting and identifying various parasitic infections [20].
During that period, the utilization of polymerase chain reaction (PCR) was still restricted, with most studies focusing on malaria, leishmania, trypanosome, and toxoplasma parasites, all of which are tissue parasites. Furthermore, with the exception of toxoplasmosis, the application of PCR on DNA extracted directly from patient samples was limited. In the past decade or so, numerous clinical microbiology laboratories have been equipped with the necessary tools to conduct molecular diagnostics [21]. Technical advancements, particularly the introduction of real-time PCR, have addressed many of the challenges associated with early PCR methods, such as the risk of contamination from amplified products. Additionally, the ability to incorporate multiple targets in a single multiplex assay has become more straightforward. The implementation of automated DNA/RNA isolation techniques has enabled the use of nucleic acid-based detection methods in a high-throughput manner. Various molecular detection, differentiation, and genotyping techniques for numerous parasites have been developed and integrated into both diagnostic and research environments.
4.1 Techniques of DNA isolation
In the absence of a suitable nucleic acid isolation method, the reliability of DNA amplification techniques is compromised. It is imperative to consider two key factors. Firstly, the isolation method must effectively liberate nucleic acids from the parasitic stage present in the clinical sample, such as cysts, spores, or eggs. Secondly, the isolated nucleic acids should be devoid of any substances that could impede or hinder the amplification reaction. This is particularly crucial when isolating parasite DNA from complex matrices like feces [22].
Various strategies can be employed to prevent inhibition of the amplification reaction, such as heating the stool specimen, incorporating absorbent substances like polyvinyl polypyrrolidone, or utilizing inhibitor-resistant DNA polymerases in the PCR mixture [21, 23, 24, 25]. Additionally, the inclusion of an internal inhibition control in each reaction mixture is essential. For instance, the use of phocin herpesvirus (PhHV) as a control allows for monitoring of inhibition within the amplification process [26].
Maintaining consistency in the amplification cycles across samples is also crucial, as any deviation may indicate inhibition. In such instances, repeating the DNA isolation and PCR processes using a diluted sample is recommended. The efficient release of nucleic acids is contingent upon a well-balanced approach in the DNA isolation procedure.
The amplification of a target sequence in PCR relies on the activity of a DNA polymerase enzyme, which catalyzes the synthesis of new DNA molecules by adding free nucleotides to a pre-existing DNA template. Primers play a crucial role in initiating DNA synthesis by providing a starting point for the polymerase. These primers are short, single-stranded nucleic acid sequences typically consisting of 16–30 base pairs that are designed to be complementary to the specific target sequence being amplified.
During PCR, the polymerase enzyme initiates replication at the 3′-end of the primer and proceeds to synthesize a new DNA strand that is complementary to the target sequence. This process allows for the selective amplification of the desired DNA target, enabling the detection and analysis of specific genetic sequences [27].
4.2 Conventional PCR
Conventional PCR, also known as traditional PCR, is a widely used molecular biology technique that amplifies a specific segment of DNA through a series of temperature cycles. This method involves the use of a DNA template, primers, DNA polymerase, and nucleotides to generate multiple copies of the target DNA sequence. The conventional polymerase chain reaction (PCR) plays a crucial role in the accurate diagnosis of intestinal parasites. By targeting specific DNA sequences of the parasites, conventional PCR can detect even low levels of infection with high sensitivity and specificity. This method is particularly valuable in cases where traditional diagnostic techniques may yield false-negative results. The precision and reliability of conventional PCR make it an indispensable tool in the identification and management of intestinal parasite infections. Conventional PCR offers a sensitive and specific method for the diagnosis of intestinal parasites like
However, there are several limitations associated with conventional PCR in the diagnosis of intestinal parasites. One major drawback is the potential for false-negative results due to the presence of PCR inhibitors in the sample. Additionally, conventional PCR may not be able to detect all species of intestinal parasites, leading to incomplete or inaccurate diagnoses. Furthermore, the sensitivity and specificity of conventional PCR can be affected by variations in sample collection, storage, and processing techniques.
4.3 Reverse transcriptase PCR
To enhance the capabilities of PCR amplification to the transcriptome level, the initial step involves the reverse transcription of RNA into complementary DNA (cDNA). Reverse transcriptase PCR (RT-PCR) emerges as a superior method for scrutinizing RNA transcripts, particularly when dealing with limited quantities of starting material. In contrast, traditional blotting hybridization assays necessitate a larger amount of RNA for analysis and lack the efficiency and convenience provided by PCR-based techniques. RT-PCR boasts numerous advantages, including its adaptability, sensitivity, swift processing time, and the ability to concurrently compare multiple samples. Within the realm of reverse transcriptase PCR (RT-PCR), cDNA replicas are generated from RNA, followed by the standard PCR amplification of the desired target.
Reverse transcriptase PCR (RT-PCR) plays a crucial role in the diagnosis of intestinal parasites. This molecular technique allows for the detection of parasite genetic material in clinical samples, providing a highly sensitive and specific method for identifying infections. By targeting specific RNA sequences of the parasite, RT-PCR can accurately differentiate between different parasite species and strains. This precision is essential for guiding appropriate treatment strategies and monitoring the effectiveness of interventions. In addition, RT-PCR can detect low levels of parasite DNA, making it particularly useful in cases of low parasite burden or chronic infections. Overall, the use of RT-PCR in the diagnosis of intestinal parasites represents a valuable tool in the clinical management of these infections.
4.4 Real-time PCR
Real-time PCR, or quantitative PCR, is a powerful molecular biology technique used to quantify and monitor the amplification of specific DNA sequences in real time. This technique allows researchers to accurately measure the amount of DNA present in a sample at each cycle of the PCR reaction, providing precise and quantitative results. Real-time PCR is widely used in research, clinical diagnostics, and forensic analysis due to its sensitivity, specificity, and speed. It has revolutionized the field of molecular biology by enabling rapid and accurate detection of genetic material in a wide range of applications.
In the realm of real-time PCR, the quantification of amplicons occurs in “real time” as the amplification process unfolds. Various techniques have been developed, ranging from the utilization of non-specific staining of double-stranded DNA with intercalating dyes to the incorporation of fluorescence-labeled DNA probes.
A significant advancement in the field of diagnostic applications of PCR was the emergence of real-time or quantitative PCR (qPCR) assays. This development led to the rapid introduction of various detection chemistries for real-time PCR, resulting in the gradual disappearance of older detection methods such as gel electrophoresis and allele-specific oligonucleotide blots from laboratory practices. qPCR integrates the amplification steps of traditional PCR with simultaneous detection steps that eliminate the need for post-PCR manipulation, as the PCR process is directly monitored within the reaction vessel.
In qPCR, the exponential phase of PCR is closely monitored in real time using fluorescently labeled molecules, allowing for the direct correlation between the amount of PCR product present in the reaction vessel and the emitted fluorescence, as well as the initial target quantity. This quantitative aspect of qPCR makes it a valuable tool in molecular diagnostics.
There are two primary types of detection chemistries utilized in qPCR: those employing intercalating DNA binding dyes like SYBR Green I, and those utilizing various fluorescently labeled probes such as TaqMan. The key advantages of qPCR include the rapid analysis of samples without the need for post-PCR processing steps, the closed-tube design that minimizes the risk of contamination, and its quantitative capabilities.
Following qPCR, two main post-analysis methods are commonly employed: amplification curve analysis for quantifying the amount of amplicon by comparison to a known standard, and melt curve analysis based on the denaturation property of double-stranded DNA with heat. This denaturation process is monitored using fluorescent dyes that emit fluorescence when bound to double-stranded DNA.
As the temperature is increased, the double strand begins to dissociate, releasing the dye and causing a decrease in fluorescence intensity. The resulting fluorescence data is depicted as a curve of fluorescence intensity plotted against temperature. The melting temperature (Tm) is the point at which 50% of the DNA is in the double-stranded state, and it is indicated by the peak of the melting curve derivative. When DNA binding dyes are present in saturating concentrations, a specific amplicon sequence will exhibit a distinct Tm and melting curve shape. This unique melting curve can be utilized to identify DNA sequence variations within the amplicon without the need for post-PCR processing.
The streamlined nature of probe-based real-time PCR chemistry, such as scorpion probes, reduces the risk of contamination, minimizes labor time, and optimizes reagent costs, making it a valuable tool in molecular biology research [28, 29]. The individual quantification of probes utilizing distinct fluorophores that emit fluorescence at varying wavelengths facilitates the execution of multiplex polymerase chain reactions (PCRs) involving DNA fragments of comparable sizes with uniform efficacy.
The advancement of high-resolution qPCR instruments and novel saturating DNA dyes has enabled a more accurate assessment of sequence variations through melting analysis. High-resolution melting analysis (HRMA) can differentiate DNA sequences based on factors such as composition, length, GC content, and strand complementarity. It is valuable for mutation scanning, methylation studies, and genotyping. The method’s ease of use, high sensitivity and specificity, cost-effectiveness, and rapid turnaround time make it well-suited for routine diagnostic applications. However, the accuracy of HRMA is contingent upon the quality of the instrumentation, saturation dyes, and analysis software employed, potentially leading to variability in different clinical diagnostic settings [30, 31].
Real-time PCR plays a crucial role in the diagnosis of intestinal parasites by providing a rapid and accurate method for detecting the presence of these pathogens in clinical samples. This advanced molecular technique allows for the amplification and quantification of specific DNA sequences from parasites, enabling healthcare professionals to identify the exact species causing the infection. Real-time PCR is particularly beneficial in cases where traditional microscopy techniques may yield false-negative results or fail to differentiate between similar parasite species. By offering high sensitivity and specificity, real-time PCR aids in the timely and precise diagnosis of intestinal parasites, ultimately guiding appropriate treatment strategies for patients.
4.5 Multiplex PCR
Another significant advancement in the progression of PCR technology is the enhancement of assay multiplexing capabilities. Multiplex PCR is a highly effective technique that enables the amplification of two or more products simultaneously within a single reaction tube. This method typically involves the utilization of different primer or probe pairs in the same reaction to amplify multiple targets concurrently.
Multiplex PCR is extensively utilized in various genotyping applications and across multiple areas of DNA testing within research, forensic, and diagnostic laboratories. Its applications range from gene expression and deletion analysis to SNP genotyping, forensic identity testing such as STR typing, and pathogen detection. The ability to quantify multiple genes within a single reaction not only reduces reagent costs and conserves sample material but also enhances throughput capabilities [27].
Multiplex PCR plays a crucial role in the diagnosis of intestinal parasites by allowing for the simultaneous detection of multiple parasite species in a single test. This advanced molecular technique offers increased sensitivity and specificity compared to traditional methods, enabling healthcare providers to accurately identify a wide range of parasites in a timely manner. By detecting multiple parasites at once, multiplex PCR streamlines the diagnostic process and helps guide appropriate treatment decisions for patients with suspected intestinal parasitic infections. Its ability to identify a diverse array of parasites makes it an invaluable tool in the field of diagnostic medicine, providing healthcare professionals with a comprehensive and efficient approach to diagnosing intestinal parasites.
4.6 Random amplified polymorphic DNA
Random amplification of polymorphic DNA (RAPD) is conducted using single primers with arbitrarily selected short nucleotide sequences to amplify products from genomic DNA. Following optimization, distinct banding patterns specific to genus, species, or strain can be observed, representing various DNA regions across the entire genome. The utilization of these non-specific primers necessitates DNA from a pure isolate free from contamination by DNA from other organisms, rendering this method unsuitable for genomic DNA extracted from clinical samples. Specific DNA products can be isolated, sequenced, and utilized for the development of targeted assays [32].
Random amplified polymorphic DNA (RAPD) analysis plays a crucial role in the diagnosis of intestinal parasites by providing a highly sensitive and specific method for detecting genetic variations within parasite populations. This technique allows for the identification of unique DNA markers that can differentiate between different parasite species, strains, or isolates. By analyzing the RAPD profiles of parasite samples, healthcare professionals can accurately diagnose and monitor infections, track the spread of parasites, and assess the effectiveness of treatment strategies.
Addressing the limitations of current molecular techniques, Next-generation sequencing (NGS) was introduced. NGS is a cutting-edge technology that allows for rapid and high-throughput sequencing of DNA or RNA. This advanced method has revolutionized the field of genomics by enabling researchers to efficiently analyze large amounts of genetic information in a shorter amount of time. Next-generation sequencing has opened up new possibilities for studying complex biological processes, identifying genetic variations associated with diseases, and advancing personalized medicine.
NGS has revolutionized the rapid generation of extensive data from parasitic species in a single individual, population, or environmental sample within a single sequencing run. NGS technologies have emerged as robust tools for comprehensive parasite detection and genomic analysis [33, 34]. NGS offers numerous advantages over traditional Sanger sequencing, including high throughput, cost-effectiveness, rapid processing, enhanced sensitivity (detecting as low as ~10 ng DNA), and decreased labor to mitigate cloning bias. Platforms like Illumina and Oxford Nanopore can sequence complete parasite genomes from clinical samples, yielding crucial insights into parasite diversity, drug resistance, and transmission dynamics. Furthermore, metagenomic strategies enable the concurrent detection of multiple pathogens in complex clinical specimens, improving diagnostic accuracy in cases of polyparasitism.
5. Imaging studies
Imaging plays a pivotal role in the diagnosis of intestinal parasites, providing a range of techniques to visualize the gastrointestinal tract and identify parasitic infections. Radiographic imaging methods, including X-rays, barium studies, and computed tomography (CT) scans, can unveil structural abnormalities in the gastrointestinal tract resulting from parasitic infections. Specific parasites, such as Ascaris lumbricoides (roundworm), may be discernible on abdominal X-rays due to their distinctive appearance, aiding in the diagnostic process. Barium studies, encompassing barium swallow and barium enema, can pinpoint irregularities like strictures or obstructions caused by large parasites or their associated complications [35].
Ultrasonography proves particularly valuable in detecting liver and biliary tract involvement in parasitic infections, such as liver flukes (e.g.,
Recently, Capsule endoscopy involves the ingestion of a pill-sized camera that captures images as it traverses the digestive tract, providing a comprehensive view of the small intestine. This non-invasive procedure is particularly valuable for diagnosing small bowel parasitic infections, such as hookworms (e.g.,
Furthermore, the integration of various imaging modalities or contrast agents for the simultaneous detection of multiple parasites or gastrointestinal abnormalities, along with the utilization of nanoparticles that are specifically tailored to bind to parasite antigens, holds promise for enhancing the sensitivity of parasite detection in imaging techniques.
6. Nanoparticles in the diagnosis of intestinal parasites
Nanoparticles are minuscule particles with dimensions on the nanometer scale, typically ranging from 1 to 100 nanometers in size. These particles exhibit unique physical and chemical properties due to their small size, high surface area-to-volume ratio, and quantum effects. Nanoparticles, owing to their distinctive physical and chemical attributes, have generated considerable interest in the realm of biomedical applications, particularly in disease diagnosis. In the domain of intestinal parasites, nanoparticles present a plethora of benefits, including high sensitivity, specificity, and adaptability. Various diagnostic methodologies for detecting intestinal parasites have leveraged the advantages offered by nanoparticles, encompassing:
Immunoassays: nanoparticles adorned with antibodies or antigens tailored to parasite biomarkers facilitate the highly sensitive detection of parasite antigens in clinical specimens. Immunoassays such as enzyme-linked immunosorbent assays (ELISA) and lateral flow assays (LFAs) expedite the specific identification of parasite proteins or antigens in stool samples, thereby expediting early diagnosis.
Nucleic acid detection: nanoparticles coupled with nucleic acid probes, such as DNA or RNA aptamers, enable the precise detection of parasite DNA or RNA sequences with exceptional sensitivity and specificity. This approach, often integrated with polymerase chain reaction (PCR) or loop-mediated isothermal amplification (LAMP), enables the swift and accurate identification of parasite genetic material in clinical samples.
Imaging and contrast agents: nanoparticles possessing imaging capabilities, such as quantum dots, gold nanoparticles, and magnetic nanoparticles, function as contrast agents for imaging modalities like fluorescence microscopy, computed tomography (CT), and magnetic resonance imaging (MRI). These nanoparticles can be customized with targeting ligands to specifically target and visualize parasites in the gastrointestinal tract, thereby facilitating diagnostic imaging and localization.
Recent research efforts have been devoted to the development of innovative nanoparticle-based diagnostic platforms for intestinal parasites. Nanostructured biosensors, which incorporate nanoparticles into biosensor platforms, enable label-free and real-time detection of parasite biomarkers in clinical samples. Biosensors utilizing surface plasmon resonance (SPR), impedance spectroscopy, and electrochemical techniques offer rapid and sensitive detection of parasite antigens or nucleic acids, with potential applications in point-of-care diagnostics.
Theranostic nanoparticles, capable of both diagnosis and therapy, show promise for targeted treatment of intestinal parasitic infections. These multifunctional nanoparticles can deliver therapeutic agents, such as antiparasitic drugs or immunomodulators while facilitating non-invasive imaging for disease monitoring and assessment of treatment response.
The utilization of nanotechnology presents numerous unique opportunities for enhanced diagnostics of parasitic diseases in the future. Current diagnostic tools for detecting parasitic diseases include light and fluorescence microscopy, rapid diagnostic tests (RDT) like immunochromatographic lateral flow tests, serology, quantitative Buffy-coat (QBC) techniques, and nucleic acid amplification techniques such as polymerase chain reaction (PCR) [36, 37, 38, 39]. Various types of nanoparticles, including fluorescent, magnetic, and metal nanoparticles, are being investigated for their diagnostic potential. Among these, gold and silver nanoparticles are the most extensively studied, as they exhibit intense absorption when stimulated by electromagnetic radiation [40]. Molecules like antibodies, antigens, and enzymes can be attached to nanoparticles as electrochemical markers, optical probes, and signal enhancers. For instance, magnetic nanoparticles with an iron oxide core and silver coating are being explored for early detection of malaria [41, 42].
7. Artificial intelligence and machine
Deep technology, also known as deep tech, currently lacks a universally accepted formal definition. However, it can be understood as a fusion of science, engineering, and design, aimed at providing societal benefits that surpass those of individual technologies [43]. This interdisciplinary approach is geared toward generating innovative solutions in various sectors such as healthcare, agriculture, space, and energy [44, 45, 46]. Deep tech projects are rooted in problem-focused research, with a focus on creating unique and complex products that are challenging to replicate. Cutting-edge technologies like machine learning, artificial intelligence, robotics, and quantum computing play a pivotal role in the design, development, and testing of these advanced solutions [47].
The integration of artificial intelligence (AI) and machine learning algorithms into diagnostic platforms is becoming increasingly prevalent, aimed at enhancing accuracy and efficiency. AI-based image analysis software is now capable of swiftly analyzing microscopic images of stool samples, accurately detecting and quantifying parasite eggs, cysts, and larvae. Furthermore, AI algorithms, trained on extensive datasets, can assist healthcare providers in interpreting intricate diagnostic results, offering diagnostic recommendations and treatment guidelines tailored to individual patient parameters. The field of medical diagnostics is undergoing a profound transformation with the advent of artificial intelligence (AI).
A study titled “Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network” sheds light on this paradigm shift, focusing on the pivotal role of convolutional neural networks (CNN) in parasitology. The findings of the study are unequivocal: the CNN model exhibited remarkable accuracy, successfully identifying parasites in specimens that had previously eluded detection through manual methods. This underscores the immense potential of AI in significantly enhancing diagnostic precision [48].
A significant increase in literature has been observed regarding the research, development, and utilization of deep tech innovations in the identification of parasites (both single and multispecies in a sample), detection of life cycle stages, and classification of eggs from human intestinal parasites [49, 50, 51]. There has been a particular focus on the application of deep learning for the analysis of protozoan images, leading to highly sensitive parasite detection. This has facilitated the creation of extensive public datasets for various parasites such as plasmodium, toxoplasma, leishmania, and trypanosome [52, 53, 54].
Within the framework of the Department of Biotechnology (DBT), advanced machine learning modules, both supervised and unsupervised, have been established and trained with vast amounts of data using artificial intelligence algorithms and neural network models. These modules have been seamlessly integrated into user-friendly interfaces, including mobile applications, resulting in unparalleled performance with no interpretation bias [55]. A groundbreaking approach utilizing computer vision screening and visualization algorithms analyzed over 19.6 billion floating point operations (flops) of digitized blood smears, achieving an impressive 99.52% accuracy in detecting malarial parasites [56].
Furthermore, a more computationally efficient model requiring only 4600 flops demonstrated a 99.23% accuracy rate, highlighting its enhanced commercial viability [56]. Deep technologies are also delving into the assessment of parasitic motility as a biomarker for precise parasite detection [57]. Zhang et al. developed a platform utilizing lensless holographic speckle analysis and deep learning to automatically detect and count motile parasites in body fluids by analyzing holographic time-lapse speckle patterns [58].
Despite the significant research and development progress in the field of deep technologies, the commercial utilization of these advancements remains relatively constrained, with minimal indications of widespread market adoption. An example of a cutting-edge commercial tool within this realm is the VETSCAN IMAGYST scanning and analyzing systems. When utilized in conjunction with the VETSCAN IMAGYST fecal preparation techniques, this innovative system enables the swift and accurate detection of Ancylostoma, Toxocara, Trichuris vulpis, and taeniid eggs in the fecal matter of both dogs and cats, all within a mere 15-minute timeframe and without the necessity for highly specialized personnel [59].
8. Challenges and future directions
Despite the considerable advancements in diagnostic methodologies, obstacles persist in the integration of these technologies into everyday clinical practice, especially in resource-limited environments. Challenges such as financial constraints, infrastructure demands, and the necessity for skilled personnel may impede widespread utilization. Furthermore, continued endeavors are essential to authenticate and establish standardized novel diagnostic assays, guaranteeing their dependability and consistency across various contexts.
9. Conclusion
Recent advancements in diagnostic techniques present promising opportunities for the precise and timely detection of intestinal parasites. Molecular methods, point-of-care testing (POCT) devices, nanoparticles, and artificial intelligence-driven approaches hold the potential to transform parasite diagnosis, ultimately enhancing patient outcomes and bolstering the efficacy of parasitic infection control measures. Nevertheless, overcoming current obstacles and ensuring equal access to these innovations are imperative for their effective deployment across a range of healthcare environments. Continued research and collaboration are necessary to refine and incorporate these diagnostic tools into standard clinical protocols, thereby playing a pivotal role in the worldwide campaign against intestinal parasitic diseases.
Acknowledgments
The author acknowledges the use of Grammarly software for language polishing of the manuscript.
Abbreviations
artificial intelligence | |
convolutional neural networks | |
computed tomography | |
department of biotechnology | |
esophagogastroduodenoscopy | |
enzyme-linked immunosorbent assay | |
lateral flow assays | |
magnetic resonance imaging | |
next-generation sequencing | |
polymerase chain reaction | |
point-of-care testing | |
rapid diagnostic tests |
References
- 1.
Charlier J, Rinaldi L, Musella V, Ploeger HW, Chartier C, Vineer HR, et al. Initial assessment of the economic burden of major parasitic helminth infections to the ruminant livestock industry in Europe. Preventive Veterinary Medicine. 2020; 182 :105103 - 2.
Pullan R, Brooker S. The health impact of polyparasitism in humans: Are we under-estimating the burden of parasitic diseases? Parasitology. 2008; 135 (7):783-794 - 3.
van der Giessen J, Deksne G, Gómez-Morales MA, Troell K, Gomes J, Sotiraki S, et al. Surveillance of foodborne parasitic diseases in Europe in a one health approach. Parasite Epidemiology and Control. 2021; 13 :e00205 - 4.
Torgerson PR, Macpherson CNL. The socioeconomic burden of parasitic zoonoses: Global trends. Veterinary Parasitology. 2011; 182 (1):79-95 - 5.
Torgerson PR, Devleesschauwer B, Praet N, Speybroeck N, Willingham AL, Kasuga F, et al. World Health Organization estimates of the global and regional disease burden of 11 foodborne parasitic diseases, 2010: A data synthesis. PLoS Medicine. 2015; 12 (12):e1001920 - 6.
Hotez PJ, Brown AS. Neglected tropical disease vaccines. Biologicals. 2009; 37 (3):160-164 - 7.
CDC – DPDx – Parasites A-Z Index. Google Search. 2021. Available from: https://www.cdc.gov/dpdx/az.html [Accessed: November 20, 2021] - 8.
Schistosomiasis and soil-transmitted helminthiases: Numbers of people treated in 2017. Available from: https://www.who.int/publications/i/item/who-wer9350essed [Accessed: Novenber 20, 2021] - 9.
Pullan RL, Smith JL, Jasrasaria R, Brooker SJ. Global numbers of infection and disease burden of soil transmitted helminth infections in 2010. Parasites & Vectors. 2014; 7 (1):37 - 10.
Dematei A, Fernandes R, Soares R, Alves H, Richter J, Botelho MC. Angiogenesis in Schistosoma haematobium -associated urinary bladder cancer. APMIS. 2017;125 (12):1056-1062 - 11.
Marcilla A, Trelis M, Cortés A, Sotillo J, Cantalapiedra F, Minguez MT, et al. Extracellular vesicles from parasitic helminths contain specific excretory/secretory proteins and are internalized in intestinal host cells. PLoS One. 2012; 7 (9):e45974 - 12.
Hart BL, Hart LA. How mammals stay healthy in nature: The evolution of behaviours to avoid parasites and pathogens. Philosophical Transactions of the Royal Society B: Biological Sciences. 2018; 373 (1751):20170205 - 13.
Baltrušis P, Höglund J. Digital PCR: Modern solution to parasite diagnostics and population trait genetics. Parasites & Vectors. 2023; 16 (1):143 - 14.
Bennett A, Garcia E, Schulze M, Bailey M, Doyle K, Finn W, et al. Building a laboratory workforce to meet the future: ASCP task force on the laboratory professionals workforce. American Journal of Clinical Pathology. 2014; 141 (2):154-167 - 15.
Petti CA, Polage CR, Quinn TC, Ronald AR, Sande MA. Laboratory medicine in Africa: A barrier to effective health care. Clinical Infectious Diseases. 2006; 42 (3):377-382 - 16.
Saiki RK, Gelfand DH, Stoffel S, Scharf SJ, Higuchi R, Horn GT, et al. Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase. Science. 1988; 239 (4839):487-491 - 17.
Saiki RK, Scharf S, Faloona F, Mullis KB, Horn GT, Erlich HA, et al. Enzymatic amplification of β-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science. 1985; 230 (4732):1350-1354 - 18.
Barker RH. DNA probe diagnosis of parasitic infections. Experimental Parasitology. 1990; 70 (4):494-499 - 19.
de Bruijn MHL. Diagnostic DNA amplification no respite for the elusive parasite. Parasitology Today. 1988; 4 (10):293-295 - 20.
Weiss JB. DNA probes and PCR for diagnosis of parasitic infections. Clinical Microbiology Reviews. 1995; 8 (1):113-130 - 21.
Verweij JJ, Stensvold CR. Molecular testing for clinical diagnosis and epidemiological investigations of intestinal parasitic infections. Clinical Microbiology Reviews. 2014; 27 (2):371-418 - 22.
Monteiro L, Bonnemaison D, Vekris A, Petry KG, Bonnet J, Vidal R, et al. Complex polysaccharides as PCR inhibitors in feces: Helicobacter pylori model. Journal of Clinical Microbiology. 1997;35 (4):995-998 - 23.
Demeler J, Ramünke S, Wolken S, Ianiello D, Rinaldi L, Gahutu JB, et al. Discrimination of gastrointestinal nematode eggs from crude fecal egg preparations by inhibitor-resistant conventional and real-time PCR. PLoS One. 2013; 8 (4):e61285 - 24.
Morgan UM, Pallant L, Dwyer BW, Forbes DA, Rich G, Thompson RCA. Comparison of PCR and microscopy for detection of Cryptosporidium parvum in human fecal specimens: Clinical trial. Journal of Clinical Microbiology. 1998;36 (4):995-998 - 25.
Kreader CA. Relief of amplification inhibition in PCR with bovine serum albumin or T4 gene 32 protein. Applied and Environmental Microbiology. 1996; 62 (3):1102-1106 - 26.
Niesters HGM. Clinical virology in real time. Journal of Clinical Virology. 2002; 25 :3-12 - 27.
Al-Turkmani MR, Deharvengt SJ, Lefferts JA. Chapter 31 – Molecular assessment of human diseases in the clinical laboratory. In: Coleman WB, Tsongalis GJ, editors. Essential Concepts in Molecular Pathology. 2nd ed. Lebanon, NH, United States: Dartmouth Hitchcock Medical Center; 2020. pp. 563-578. Available from: https://www.sciencedirect.com/science/article/pii/B9780128132579000310 - 28.
Espy MJ, Uhl JR, Sloan LM, Buckwalter SP, Jones MF, Vetter EA, et al. Real-time PCR in clinical microbiology: Applications for routine laboratory testing. Clinical Microbiology Reviews. 2006; 19 (1):165-256 - 29.
Klein D. Quantification using real-time PCR technology: Applications and limitations. Trends in Molecular Medicine. 2002; 8 (6):257-260 - 30.
Schaaf CP, Wiszniewska J, Beaudet al. Copy number and SNP arrays in clinical diagnostics. Annual Review of Genomics and Human Genetics. 2011; 12 (1):25-51 - 31.
Whale AS, Huggett JF, Cowen S, Speirs V, Shaw J, Ellison S, et al. Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation. Nucleic Acids Research. 2012; 40 (11):e82 - 32.
Williams JGK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Research. 1990; 18 (22):6531-6535 - 33.
Hutchison CA III. DNA sequencing: Bench to bedside and beyond †. Nucleic Acids Research. 2007; 35 (18):6227-6237 - 34.
Ekblom R, Galindo J. Applications of next generation sequencing in molecular ecology of non-model organisms. Heredity. 2011; 107 (1):1-15 - 35.
Palmer PES. Diagnostic imaging in parasitic infections. Pediatric Clinics of North America. 1985; 32 (4):1019-1040 - 36.
Tangpukdee N, Duangdee C, Wilairatana P, Krudsood S. Malaria diagnosis: A brief review. The Korean Journal of Parasitology. 2009; 47 (2):93-102 - 37.
Yetisgin AA, Cetinel S, Zuvin M, Kosar A, Kutlu O. Therapeutic nanoparticles and their targeted delivery applications. Molecules. 2020; 25 (9):2193 - 38.
Moyano A, Serrano-Pertierra E, Salvador M, Martínez-García JC, Rivas M, Blanco-López MC. Magnetic lateral flow immunoassays. Diagnostics. 2020; 10 (5):288 - 39.
Thakur S, Joshi J, Kaur S. Leishmaniasis diagnosis: An update on the use of parasitological, immunological and molecular methods. Journal of Parasitic Diseases. 2020; 44 (2):253-272 - 40.
Tallury P, Malhotra A, Byrne LM, Santra S. Nanobioimaging and sensing of infectious diseases. Advanced Drug Delivery Reviews. 2010; 62 (4):424-437 - 41.
Nash MA, Waitumbi JN, Hoffman AS, Yager P, Stayton PS. Multiplexed enrichment and detection of malarial biomarkers using a stimuli-responsive iron oxide and gold nanoparticle reagent system. ACS Nano. 2012; 6 (8):6776-6785 - 42.
Baptista V, Peng WK, Minas G, Veiga MI, Catarino SO. Review of microdevices for hemozoin-based malaria detection. Biosensors. 2022; 12 (2):110 - 43.
Lee K. Philosophy and Revolutions in Genetics: Deep Science and Deep Technology. London, UK: Palgrave Macmillan; 2003 - 44.
Verma J. Deep Technologies using big data in: Energy and waste management. In: Kadyan V, Singh TP, Ugwu C, editors. Deep Learning Technologies for the Sustainable Development Goals: Issues and Solutions in the Post-COVID Era. Singapore: Springer Nature; 2023. pp. 21-39. (Advanced Technologies and Societal Change). DOI: 10.1007/978-981-19-5723-9_2 - 45.
Hinton G. Deep learning—A technology with the potential to transform health care. Journal of the American Medical Association. 2018; 320 (11):1101-1102 - 46.
Lee K. The Natural and the Artefactual: The Implications of Deep Science and Deep Technology for Environmental Philosophy. United States: Lexington Books; 1999. 310 p - 47.
Patil T, Pandey S, Visrani K. A review on basic deep learning technologies and applications. In: Kotecha K, Piuri V, Shah HN, Patel R, editors. Data Science and Intelligent Applications. Singapore: Springer Singapore; 2021. pp. 565-573. (Lecture Notes on Data Engineering and Communications Technologies; vol. 52). Available from: http://link.springer.com/10.1007/978-981-15-4474-3_61 - 48.
Mathison BA, Kohan JL, Walker JF, Smith RB, Ardon O, Couturier MR. Detection of intestinal protozoa in trichrome-stained stool specimens by use of a deep convolutional neural network. Journal of Clinical Microbiology. 26 May 2020; 58 (6):e02053-19 - 49.
Zhang Y, Jiang H, Ye T, Juhas M. Deep learning for imaging and detection of microorganisms. Trends in Microbiology. 2021; 29 (7):569-572 - 50.
Butploy N, Kanarkard W, Maleewong IP. Deep learning approach for Ascaris lumbricoides parasite egg classification. Magalhães LG, editor. Journal of Parasitology Research. 2021; 2021 :1-8 - 51.
Routledge & CRC Press [Internet]. Computational Vision and Medical Image Processing V: Proceedings of the 5th Eccomas Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE 2015, Tenerife, Spain, October 19-21, 2015). Available from: https://www.routledge.com/Computational-Vision-and-Medical-Image-Processing-V-Proceedings-of-the/Tavares-Natal-Jorge/p/book/9781138029262 - 52.
Quinn JA, Nakasi R, Mugagga PKB, Byanyima P, Lubega W, Andama A. Deep convolutional neural networks for microscopy-based point of care diagnostics. In: Proceedings of the 1st Machine Learning for Healthcare Conference. Los Angeles, CA: PMLR; 2016. pp. 271-281. Available from: https://proceedings.mlr.press/v56/Quinn16.html - 53.
Ljosa V, Sokolnicki KL, Carpenter AE. Annotated high-throughput microscopy image sets for validation. Nature Methods. 2012; 9 (7):637-637 - 54.
Anantrasirichai N, Chalidabhongse TH, Palasuwan D, Naruenatthanaset K, Kobchaisawat T, Nunthanasup N, et al. ICIP 2022 challenge on parasitic egg detection and classification in microscopic images: Dataset, methods and results. In: 2022 IEEE International Conference on Image Processing (ICIP). Bordeaux, France: IEEE; 2022. pp. 4306-4310. Available from: https://ieeexplore.ieee.org/document/9897267/ - 55.
Jo T. Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning [Internet]. Cham: Springer International Publishing; 2021 [cited 2024 Oct 10]. Available from: http://link.springer.com/10.1007/978-3-030-65900-4 - 56.
Fuhad KMF, Tuba JF, Sarker MRA, Momen S, Mohammed N, Rahman T. Deep learning based automatic malaria parasite detection from blood smear and its smartphone based application. Diagnostics. 2020; 10 (5):329 - 57.
Zhang Y, Koydemir HC, Shimogawa MM, Yalcin S, Guziak A, Liu T, et al. High-throughput and label-free detection of motile parasites in bodily fluids using lensless time-resolved speckle imaging. In: Conference on Lasers and Electro-Optics (2019), Paper ATu4K2. Optica Publishing Group; 2019. p. ATu4K.2. Available from: https://opg.optica.org/abstract.cfm?uri=CLEO_AT-2019-ATu4K.2 - 58.
Zhang Y, Ceylan Koydemir H, Shimogawa MM, Yalcin S, Guziak A, Liu T, et al. Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning. Light: Science & Applications. 2018; 7 (1):108 - 59.
Nagamori Y, Hall Sedlak R, DeRosa A, Pullins A, Cree T, Loenser M, et al. Evaluation of the VETSCAN IMAGYST: An in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm. Parasites & Vectors. 2020; 13 (1):346