Three-dimensional visualization and a deep-learning model reveal complex fungal parasite networks in behaviorally manipulated ants

A decision support system for the detection of cutaneous fungal infections using artificial intelligence

Cutaneous fungal infections are one of the most common skin conditions, hence, the burden of determining fungal elements upon microscopic examination with periodic acid-Schiff (PAS) and Gomori methenamine silver (GMS) stains, is very time consuming. Despite some morphological variability posing challenges to training artificial intelligence (AI)-based solutions, these structures are favored potential targets, enabling the recruitment of promising AI-based technologies. Herein, we present a novel AI solution for identifying skin fungal infections, potentially providing a decision support system for pathologists. Skin biopsies of patients diagnosed with a cutaneous fungal infection at the Sheba Medical Center, Israel between 2014 and 2023, were used. Samples were stained with PAS and GMS and digitized by the Philips IntelliSite scanner. DeePathology® STUDIO fungal elements were annotated and deemed as ground truth data after an overall revision by two specialist pathologists. Subsequently, they were used to create an AI-based solution, which has been further validated in other regions of interests. The study participants were divided into two cohorts. In the first cohort, the overall sensitivity of the algorithm was 0.8, specificity 0.97, F1 score 0.78; in the second, the overall sensitivity of the algorithm was 0.93, specificity 0.99, F1 score 0.95. The results obtained are encouraging as proof of concept for an AI-based fungi detection algorithm. DeePathology® STUDIO can be employed as a decision support system for pathologists when diagnosing a cutaneous fungal infection using PAS and GMS stains, thereby, saving time and money.

AI-powered microscopy image analysis for parasitology: integrating human expertise

Microscopy image analysis plays a pivotal role in parasitology research. Deep learning (DL), a subset of artificial intelligence (AI), has garnered significant attention. However, traditional DL-based methods for general purposes are data-driven, often lacking explainability due to their black-box nature and sparse instructional resources. To address these challenges, this article presents a comprehensive review of recent advancements in knowledge-integrated DL models tailored for microscopy image analysis in parasitology. The massive amounts of human expert knowledge from parasitologists can enhance the accuracy and explainability of AI-driven decisions. It is expected that the adoption of knowledge-integrated DL models will open up a wide range of applications in the field of parasitology.

Genomic comparative analysis of Ophiocordyceps unilateralis sensu lato

Ophiocordyceps unilateralis sensu lato is a common pathogenic fungus of ants. A new species, O. fusiformispora, was described based on morphology and phylogenetic evidence from five genes (SSU, LSU, TEF1α, RPB1, and RPB2). The whole genomes of O. fusiformispora, O. contiispora, O. subtiliphialida, O. satoi, O. flabellata, O. acroasca, and O. camponoti-leonardi were sequenced and annotated and compared with whole genome sequences of other species in O. unilateralis sensu lato. The basic genome-wide characteristics of the 12 species showed that the related species had similar GC content and genome size. AntiSMASH and local BLAST analyses revealed that the number and types of putative SM BGCs, NPPS, PKS, and hybrid PKS-NRPS domains for the 12 species differed significantly among different species in the same genus. The putative BGC of five compounds, namely, NG-391, lucilactaene, higginsianin B, pyripyropene A, and pyranonigrin E were excavated. NG-391 and lucilactaene were 7-desmethyl analogs of fusarin C. Furthermore, the 12 genomes had common domains, such as KS-AT-DH-MT-ER-KR-ACP and SAT-KS-AT-PT-ACP-ACP-Te. The ML and BI trees of SAT-KS-AT-PT-ACP-ACP-Te were highly consistent with the multigene phylogenetic tree in the 12 species. This study provided a method to obtain the living culture of O. unilateralis sensu lato species and its asexual formed on the basis of living culture, which was of great value for further study of O. unilateralis sensu lato species in the future, and also laid a foundation for further analysis of secondary metabolites of O. unilateralis sensu lato.

Expression of trematode-induced zombie-ant behavior is strongly associated with temperature

Parasite-induced modification of host behavior increasing transmission to a next host is a common phenomenon. However, field-based studies are rare, and the role of environmental factors in eliciting host behavioral modification is often not considered. We examined the effects of temperature, relative humidity (RH), time of day, date, and an irradiation proxy on behavioral modification of the ant Formica polyctena (Förster, 1850) by the brain-encysting lancet liver fluke Dicrocoelium dendriticum (Rudolphi, 1819). This fluke induces ants to climb and bite to vegetation by the mandibles in a state of temporary tetany. A total of 1264 individual ants expressing the modified behavior were observed over 13 non-consecutive days during one year in the Bidstrup Forests, Denmark. A sub-set of those ants (N = 172) was individually marked to track the attachment and release of infected ants in relation to variation in temperature. Infected ants primarily attached to vegetation early and late in the day, corresponding to low temperature and high RH, presumably coinciding with the grazing activity of potential herbivorous definitive hosts. Temperature was the single most important determinant for the induced phenotypic change. On warm days, infected ants altered between the manipulated and non-manipulated state multiple times, while on cool days, many infected ants remained attached to the vegetation all day. Our results suggest that the temperature sensitivity of the infected ants serves the dual purpose of exposing infected ants to the next host at an opportune time, while protecting them from exposure to high temperatures, which might increase host (and parasite) mortality.

Multiomic interpretation of fungus-infected ant metabolomes during manipulated summit disease

Camponotus floridanus ants show altered behaviors followed by a fatal summiting phenotype when infected with manipulating Ophiocordyceps camponoti-floridani fungi. Host summiting as a strategy to increase transmission is also observed with parasite taxa beyond fungi, including aquatic and terrestrial helminths and baculoviruses. The drastic phenotypic changes can sometimes reflect significant molecular changes in gene expression and metabolite concentrations measured in manipulated hosts. Nevertheless, the underlying mechanisms still need to be fully characterized. To investigate the small molecules producing summiting behavior, we infected C. floridanus ants with O. camponoti-floridani and sampled their heads for LC-MS/MS when we observed the characteristic summiting phenotype. We link this metabolomic data with our previous genomic and transcriptomic data to propose mechanisms that underlie manipulated summiting behavior in "zombie ants." This "multiomic" evidence points toward the dysregulation of neurotransmitter levels and neuronal signaling. We propose that these processes are altered during infection and manipulation based on (1) differential expression of neurotransmitter synthesis and receptor genes, (2) altered abundance of metabolites and neurotransmitters (or their precursors) with known behavioral effects in ants and other insects, and (3) possible suppression of a connected immunity pathway. We additionally report signals for metabolic activity during manipulation related to primary metabolism, detoxification, and anti-stress protectants. Taken together, these findings suggest that host manipulation is likely a multi-faceted phenomenon, with key processes changing at multiple levels of molecular organization.

Using machine learning to predict protein-protein interactions between a zombie ant fungus and its carpenter ant host

Parasitic fungi produce proteins that modulate virulence, alter host physiology, and trigger host responses. These proteins, classified as a type of "effector," often act via protein-protein interactions (PPIs). The fungal parasite Ophiocordyceps camponoti-floridani (zombie ant fungus) manipulates Camponotus floridanus (carpenter ant) behavior to promote transmission. The most striking aspect of this behavioral change is a summit disease phenotype where infected hosts ascend and attach to an elevated position. Plausibly, interspecific PPIs drive aspects of Ophiocordyceps infection and host manipulation. Machine learning PPI predictions offer high-throughput methods to produce mechanistic hypotheses on how this behavioral manipulation occurs. Using D-SCRIPT to predict host-parasite PPIs, we found ca. 6000 interactions involving 2083 host proteins and 129 parasite proteins, which are encoded by genes upregulated during manipulated behavior. We identified multiple overrepresentations of functional annotations among these proteins. The strongest signals in the host highlighted neuromodulatory G-protein coupled receptors and oxidation-reduction processes. We also detected Camponotus structural and gene-regulatory proteins. In the parasite, we found enrichment of Ophiocordyceps proteases and frequent involvement of novel small secreted proteins with unknown functions. From these results, we provide new hypotheses on potential parasite effectors and host targets underlying zombie ant behavioral manipulation.

Manduca sexta caterpillars parasitized by the wasp Cotesia congregata stop chewing despite an intact motor system

The parasitic wasp Cotesia congregata suppresses feeding in its host, the caterpillar Manduca sexta, during specific periods of wasp development. We examined both feeding behaviour and the neurophysiology of the mandibular closer muscle in parasitized and unparasitized control M. sexta to determine how the wasp may accomplish this. To test whether the wasps activated a pre-existing host mechanism for feeding cessation, we examined the microstructure of feeding behaviour in caterpillars that stopped feeding due to illness-induced anorexia or an impending moult. These microstructures were compared with that shown by parasitized caterpillars. While there were overall differences between parasitized and unparasitized caterpillars, the groups showed similar progression in feeding microstructure as feeding ended, suggesting a common pattern for terminating a meal. Parasitized caterpillars also consumed less leaf area in 100 bites than control caterpillars at around the same time their feeding microstructure changed. The decline in food consumption was accompanied by fewer spikes per burst and shorter burst durations in chewing muscle electromyograms. Similar extracellular results were obtained from the motorneuron of the mandibular closer muscle. However, chewing was dramatically re-activated in non-feeding parasitized caterpillars if the connectives posterior to the suboesophageal ganglion were severed. The same result was observed in unparasitized caterpillars given the same treatment. Our results suggest that the reduced feeding in parasitized caterpillars is not due to damage to the central pattern generator (CPG) for chewing, motor nerves or chewing muscles, but is more likely to be due to a suppression of chewing CPG activity by ascending or descending inputs.

Seeking the Psilocybiome: Psychedelics meet the microbiota-gut-brain axis

Moving towards a systems psychiatry paradigm embraces the inherent complex interactions across all levels from micro to macro and necessitates an integrated approach to treatment. Cortical 5-HT2A receptors are key primary targets for the effects of serotonergic psychedelics. However, the therapeutic mechanisms underlying psychedelic therapy are complex and traverse molecular, cellular, and network levels, under the influence of biofeedback signals from the periphery and the environment. At the interface between the individual and the environment, the gut microbiome, via the gut-brain axis, plays an important role in the unconscious parallel processing systems regulating host neurophysiology. While psychedelic and microbial signalling systems operate over different timescales, the microbiota-gut-brain (MGB) axis, as a convergence hub between multiple biofeedback systems may play a role in the preparatory phase, the acute administration phase, and the integration phase of psychedelic therapy. In keeping with an interconnected systems-based approach, this review will discuss the gut microbiome and mycobiome and pathways of the MGB axis, and then explore the potential interaction between psychedelic therapy and the MGB axis and how this might influence mechanism of action and treatment response. Finally, we will discuss the possible implications for a precision medicine-based psychedelic therapy paradigm.

H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation

Deep learning (DL) based semantic segmentation methods have achieved excellent performance in biomedical image segmentation, producing high quality probability maps to allow extraction of rich instance information to facilitate good instance segmentation. While numerous efforts were put into developing new DL semantic segmentation models, less attention was paid to a key issue of how to effectively explore their probability maps to attain the best possible instance segmentation. We observe that probability maps by DL semantic segmentation models can be used to generate many possible instance candidates, and accurate instance segmentation can be achieved by selecting from them a set of "optimized" candidates as output instances. Further, the generated instance candidates form a well-behaved hierarchical structure (a forest), which allows selecting instances in an optimized manner. Hence, we propose a novel framework, called hierarchical earth mover's distance (H-EMD), for instance segmentation in biomedical 2D+time videos and 3D images, which judiciously incorporates consistent instance selection with semantic-segmentation-generated probability maps. H-EMD contains two main stages: (1) instance candidate generation: capturing instance-structured information in probability maps by generating many instance candidates in a forest structure; (2) instance candidate selection: selecting instances from the candidate set for final instance segmentation. We formulate a key instance selection problem on the instance candidate forest as an optimization problem based on the earth mover's distance (EMD), and solve it by integer linear programming. Extensive experiments on eight biomedical video or 3D datasets demonstrate that H-EMD consistently boosts DL semantic segmentation models and is highly competitive with state-of-the-art methods.

Ultrastructural analysis of beetle larva cuticles during infection with the entomopathogenic fungus, Beauveria bassiana

BACKGROUND

Beauveria bassiana is one of the commercially available entomopathogenic fungi (EPF), and a number of isolates with high virulence and broad host spectrum have been used to control agricultural and forest pests. Although the functional importance of genes in EPFs' pathogenesis have been extensively studied, the precise ultrastructural mechanism of the fungal infection, particularly penetration of the host insect cuticles, is not well understood.

RESULTS

In this study, we investigated the morphology and ultrastructure of the larval cuticle of the red flour beetle, Tribolium castaneum, after treatment with B. bassiana ERL1170 expressing an enhanced green fluorescent protein (Bb-eGFP). The Bb-eGFP showed high virulence against the larvae, with approximately 90% mortality at 48 h after treatment (HAT) and 100% at 72 HAT under our infection conditions. In these larvae, the regions of the body wall with flexible cuticles, such as the ventral and ventrolateral thorax and abdomen, became darkly melanized, but there was little to no melanization in the rigid dorsal cuticular structures. Confocal microscopy and transmission electron microscopy (TEM) indicated that germinated conidia on the surface of the larval cuticle were evident at 6 HAT, which formed penetration pegs and began to penetrate the several cuticle layers/laminae by 12 HAT. The penetration pegs then developed invading hyphae, some of which passed through the cuticle and reached the epidermal cells by 24 HAT. The larval cuticle was aggressively and extensively disrupted by 48 HAT, and a number of outgrowing hyphae were observed at 72 HAT.

CONCLUSIONS

Our results indicate that Bb-eGFP is capable of infection and penetrating T. castaneum larvae shortly after inoculation (~24 HAT) at the body regions with apparently flexible and membranous cuticles, such as the ventral intersegmental regions and the ventrolateral pleura. This study provides details on the histopathogenesis of the host cuticle by infection and penetration of EPFs, which can facilitate the management of insect pests. © 2022 Society of Chemical Industry.

Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms

The rich variety of biological forms and behaviours results from one evolutionary history on Earth, via frozen accidents and selection in specific environments. This ubiquitous baggage in natural, familiar model species obscures the plasticity and swarm intelligence of cellular collectives. Significant gaps exist in our understanding of the origin of anatomical novelty, of the relationship between genome and form, and of strategies for control of large-scale structure and function in regenerative medicine and bioengineering. Analysis of living forms that have never existed before is necessary to reveal deep design principles of life as it can be. We briefly review existing examples of chimaeras, cyborgs, hybrots and other beings along the spectrum containing evolved and designed systems. To drive experimental progress in multicellular synthetic morphology, we propose teleonomic (goal-seeking, problem-solving) behaviour in diverse problem spaces as a powerful invariant across possible beings regardless of composition or origin. Cybernetic perspectives on chimaeric morphogenesis erase artificial distinctions established by past limitations of technology and imagination. We suggest that a multi-scale competency architecture facilitates evolution of robust problem-solving, living machines. Creation and analysis of novel living forms will be an essential testbed for the emerging field of diverse intelligence, with numerous implications across regenerative medicine, robotics and ethics.

Host Manipulation, Gene Editing, and Non-Traditional Model Organisms: A New Frontier for Behavioral Research?

Insects and parasites dominate the biosphere, in terms of known biodiversity and mode of life, respectively. Consequently, insects play a part in many host-parasite systems, either as parasite, host, or both. Moreover, a lot of these systems involve adaptive parasite-induced changes of host phenotype (typically behavior or morphology), which is commonly known as host manipulation. While many host manipulation systems have been described within the last few decades, the proximate mechanisms that underpin host phenotypic change are still largely unknown. Given the intimate co-evolutionary history of host-parasite systems, teasing apart the intricate network of biochemical reactions involved in host manipulation requires the integration of various complementary technologies. In this perspective, we stress the importance of multidisciplinary research on host manipulation, such as high-throughput sequencing methods (genomics and transcriptomics) to search for candidate mechanisms that are activated during a manipulation event. Then, we argue that gene editing technologies, specifically the CRISPR-Cas9 system, are a powerful way to test for the functional roles of candidate mechanisms, in both the parasite and the host. Finally, given the sheer diversity of unique host-parasite systems discovered to date, there is indeed a tremendous potential to create novel non-traditional model systems that could greatly expand our capacity to test the fundamental aspects of behavior and behavioral regulation.

Data-Driven Deep Supervision for Medical Image Segmentation

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-dependent difficulties such as low image contrast, noisy background, and complicated objects of interest render the segmentation problem challenging. These difficulties diminish dense prediction and make it tough for known approaches to explore data-specific attributes for robust feature extraction. In this paper, we study medical image segmentation by focusing on robust data-specific feature extraction to achieve improved dense prediction. We propose a new deep convolutional neural network (CNN), which exploits specific attributes of input datasets to utilize deep supervision for enhanced feature extraction. In particular, we strategically locate and deploy auxiliary supervision, by matching the object perceptive field (OPF) (which we define and compute) with the layer-wise effective receptive fields (LERF) of the network. This helps the model pay close attention to some distinct input data dependent features, which the network might otherwise 'ignore' during training. Further, to achieve better target localization and refined dense prediction, we propose the densely decoded networks (DDN), by selectively introducing additional network connections (the 'crutch' connections). Using five public datasets (two retinal vessel, melanoma, optic disc/cup, and spleen segmentation) and two in-house datasets (lymph node and fungus segmentation), we verify the effectiveness of our proposed approach in 2D and 3D segmentation.

Caste, Sex, and Parasitism Influence Brain Plasticity in a Social Wasp

Brain plasticity is widespread in nature, as it enables adaptive responses to sensory demands associated with novel stimuli, environmental changes and social conditions. Social Hymenoptera are particularly well-suited to study neuroplasticity, because the division of labor amongst females and the different life histories of males and females are associated with specific sensory needs. Here, we take advantage of the social wasp Polistes dominula to explore if brain plasticity is influenced by caste and sex, and the exploitation by the strepsipteran parasite Xenos vesparum. Within sexes, male wasps had proportionally larger optic lobes, while females had larger antennal lobes, which is consistent with the sensory needs of sex-specific life histories. Within castes, reproductive females had larger mushroom body calyces, as predicted by their sensory needs for extensive within-colony interactions and winter aggregations, than workers who frequently forage for nest material and prey. Parasites had different effects on female and male hosts. Contrary to our predictions, female workers were castrated and behaviorally manipulated by female or male parasites, but only showed moderate differences in brain tissue allocation compared to non-parasitized workers. Parasitized males maintained their reproductive apparatus and sexual behavior. However, they had smaller brains and larger sensory brain regions than non-parasitized males. Our findings confirm that caste and sex mediate brain plasticity in P. dominula, and that parasitic manipulation drives differential allocation of brain regions depending on host sex.

Possible impacts of the predominant Bacillus bacteria on the Ophiocordyceps unilateralis s. l. in its infected ant cadavers

Animal hosts infected and killed by parasitoid fungi become nutrient-rich cadavers for saprophytes. Bacteria adapted to colonization of parasitoid fungi can be selected and can predominate in the cadavers, actions that consequently impact the fitness of the parasitoid fungi. In Taiwan, the zombie fungus, Ophiocordyceps unilateralis sensu lato (Clavicipitaceae: Hypocreales), was found to parasitize eight ant species, with preference for a principal host, Polyrhachis moesta. In this study, ant cadavers grew a fungal stroma that was predominated by Bacillus cereus/thuringiensis. The bacterial diversity in the principal ant host was found to be lower than the bacterial diversity in alternative hosts, a situation that might enhance the impact of B. cereus/thuringiensis on the sympatric fungus. The B. cereus/thuringiensis isolates from fungal stroma displayed higher resistance to a specific naphthoquinone (plumbagin) than sympatric bacteria from the environment. Naphthoquinones are known to be produced by O. unilateralis s. l., and hence the resistance displayed by B. cereus/thuringiensis isolates to these compounds suggests an advantage to B. cereus/thuringiensis to grow in the ant cadaver. Bacteria proliferating in the ant cadaver inevitably compete for resources with the fungus. However, the B. cereus/thuringiensis isolates displayed in vitro capabilities of hemolysis, production of hydrolytic enzymes, and antagonistic effects to co-cultured nematodes and entomopathogenic fungi. Thus, co-infection with B. cereus/thuringiensis offers potential benefits to the zombie fungus in killing the host under favorable conditions for reproduction, digesting the host tissue, and protecting the cadaver from being taken over by other consumers. With these potential benefits, the synergistic effect of B. cereus/thuringiensis on O. unilateralis infection is noteworthy given the competitive relationship of these two organisms sharing the same resource.

Mechanisms behind the Madness: How Do Zombie-Making Fungal Entomopathogens Affect Host Behavior To Increase Transmission?

Transmission is a crucial step in all pathogen life cycles. As such, certain species have evolved complex traits that increase their chances to find and invade new hosts. Fungal species that hijack insect behaviors are evident examples. Many of these "zombie-making" entomopathogens cause their hosts to exhibit heightened activity, seek out elevated positions, and display body postures that promote spore dispersal, all with specific circadian timing. Answering how fungal entomopathogens manipulate their hosts will increase our understanding of molecular aspects underlying fungus-insect interactions, pathogen-host coevolution, and the regulation of animal behavior. It may also lead to the discovery of novel bioactive compounds, given that the fungi involved have traditionally been understudied. This minireview summarizes and discusses recent work on zombie-making fungi of the orders Hypocreales and Entomophthorales that has resulted in hypotheses regarding the mechanisms that drive fungal manipulation of insect behavior. We discuss mechanical processes, host chemical signaling pathways, and fungal secreted effectors proposed to be involved in establishing pathogen-adaptive behaviors. Additionally, we touch on effectors' possible modes of action and how the convergent evolution of host manipulation could have given rise to the many parallels in observed behaviors across fungus-insect systems and beyond. However, the hypothesized mechanisms of behavior manipulation have yet to be proven. We, therefore, also suggest avenues of research that would move the field toward a more quantitative future.

Wolbachia in the spittlebug Prosapia ignipectus: Variable infection frequencies, but no apparent effect on host reproductive isolation

Animals serve as hosts for complex communities of microorganisms, including endosymbionts that live inside their cells. Wolbachia bacteria are perhaps the most common endosymbionts, manipulating host reproduction to propagate. Many Wolbachia cause cytoplasmic incompatibility (CI), which results in reduced egg hatch when uninfected females mate with infected males. Wolbachia that cause intense CI spread to high and relatively stable frequencies, while strains that cause weak or no CI tend to persist at intermediate, often variable, frequencies. Wolbachia could also contribute to host reproductive isolation (RI), although current support for such contributions is limited to a few systems. To test for Wolbachia frequency variation and effects on host RI, we sampled several local Prosapia ignipectus (Fitch) (Hemiptera: Cercopidae) spittlebug populations in the northeastern United States over two years, including closely juxtaposed Maine populations with different monomorphic color forms, "black" and "lined." We discovered a group-B Wolbachia (wPig) infecting P. ignipectus that diverged from group-A Wolbachia-like model wMel and wRi strains in Drosophila-6 to 46 MYA. Populations of the sister species Prosapia bicincta (Say) from Hawaii and Florida are uninfected, suggesting that P. ignipectus acquired wPig after their initial divergence. wPig frequencies were generally high and variable among sites and between years. While phenotyping wPig effects on host reproduction is not currently feasible, the wPig genome contains three divergent sets of CI loci, consistent with high wPig frequencies. Finally, Maine monomorphic black and monomorphic lined populations of P. ignipectus share both wPig and mtDNA haplotypes, implying no apparent effect of wPig on the maintenance of this morphological contact zone. We hypothesize P. ignipectus acquired wPig horizontally as observed for many Drosophila species, and that significant CI and variable transmission produce high but variable wPig frequencies.

An agent-based model shows zombie ants exhibit search behavior

Parasites can alter the behavior of animals. Such alterations could be a byproduct of infection or actively controlled and directed by the parasite. Ants infected with zombie ant fungi (Ophiocordyceps sp.) show behavioral changes culminating in the ant dying while biting into vegetation. To investigate the influence of the parasite on behavioral changes, we created an agent-based model that provides a prediction of how fungal infected ants move before death. The model shows how alterations in movement, such as an increased turning rate, within the normal range of ant behavior, can lead a host from the nest to the underside of a leaf. This demonstrates the simplicity in how such behavioral changes could evolve, as the fungal parasite could benefit from the natural behavior of the host, contesting a hypothesis of highly directed manipulation.

Insect Behavioral Change and the Potential Contributions of Neuroinflammation-A Call for Future Research

Many organisms are able to elicit behavioral change in other organisms. Examples include different microbes (e.g., viruses and fungi), parasites (e.g., hairworms and trematodes), and parasitoid wasps. In most cases, the mechanisms underlying host behavioral change remain relatively unclear. There is a growing body of literature linking alterations in immune signaling with neuron health, communication, and function; however, there is a paucity of data detailing the effects of altered neuroimmune signaling on insect neuron function and how glial cells may contribute toward neuron dysregulation. It is important to consider the potential impacts of altered neuroimmune communication on host behavior and reflect on its potential role as an important tool in the "neuro-engineer" toolkit. In this review, we examine what is known about the relationships between the insect immune and nervous systems. We highlight organisms that are able to influence insect behavior and discuss possible mechanisms of behavioral manipulation, including potentially dysregulated neuroimmune communication. We close by identifying opportunities for integrating research in insect innate immunity, glial cell physiology, and neurobiology in the investigation of behavioral manipulation.

Deep Learning for Imaging and Detection of Microorganisms

Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenges faced by human-operated microscopy, deep-learning-based methods have been proposed for microscopic image analysis of a wide range of microorganisms, including viruses, bacteria, fungi, and parasites. We believe that deep-learning technology-based systems will be on the front line of monitoring and investigation of microorganisms.

Phase-field modeling of constrained interactive fungal networks

Fungi develop structures that interact with their surroundings and evolve adaptively in the presence of geometrical constraints, finding optimal solutions for complex combinatorial problems. The pathogenic fungus Ophiocordyceps constitutes a perfect model for the study of constrained interactive networks. Modeling these networks is challenging due to the highly coupled physics involved and their interaction with moving boundaries. In this work, we develop a computational phase-field model to elucidate the mechanics of the emerging properties observed in fungal networks. We use a variational approach to derive the equations governing the evolution in time of the mycelium biomass and the nutrients in the medium. We present an extensive testing of our model, reproduce growing and decaying phenomena, and capture spatial and temporal scales. We explore the variables interplay mechanism that leads to different colony morphologies, and explain abrupt changes of patterns observed in the laboratory. We apply our model to simulate analogous processes to the evolution of Ophiocordyceps as it grows through confined geometry and depletes available resources, demonstrating the suitability of the formulation to study this class of biological networks.

Interpreting Morphological Adaptations Associated with Viviparity in the Tsetse Fly Glossina morsitans (Westwood) by Three-Dimensional Analysis

Simple Summary

Tsetse flies, the sole transmitters of African Sleeping Sickness parasites, have a unique reproductive biology. They only develop one offspring at a time, they carry that offspring in their uterus for its entire immature development and provide nourishment for that offspring via milk-like secretions. This specialized reproductive biology has required dramatic modifications to the morphology of the reproductive organs in these and related flies. Here, we use phase contrast micro-Computed Tomography (Micro-CT) to visualize these adaptations in three dimensions for the first time. These adaptations include cuticular modifications allowing increased abdominal volume, expanded abdominal and uterine musculature, reduced egg development capacity, structural features of the male seminal secretions and detailed visualization of the gland responsible for synthesis and secretion of “milk” to feed intrauterine larvae. The ability to examine these tissues within the context of the rest of the organ systems in the fly provides new functional insights into how these changes have facilitated the evolution of the mating and reproductive biology of these flies.

Abstract

Tsetse flies (genus Glossina), the sole vectors of African trypanosomiasis, are distinct from most other insects, due to dramatic morphological and physiological adaptations required to support their unique biology. These adaptations are driven by demands associated with obligate hematophagy and viviparous reproduction. Obligate viviparity entails intrauterine larval development and the provision of maternal nutrients for the developing larvae. The reduced reproductive capacity/rate associated with this biology results in increased inter- and intra-sexual competition. Here, we use phase contrast microcomputed tomography (pcMicroCT) to analyze morphological adaptations associated with viviparous biology. These include (1) modifications facilitating abdominal distention required during blood feeding and pregnancy, (2) abdominal and uterine musculature adaptations for gestation and parturition of developed larvae, (3) reduced ovarian structure and capacity, (4) structural features of the male-derived spermatophore optimizing semen/sperm delivery and inhibition of insemination by competing males and (5) structural features of the milk gland facilitating nutrient incorporation and transfer into the uterus. Three-dimensional analysis of these features provides unprecedented opportunities for examination and discovery of internal morphological features not possible with traditional microscopy techniques and provides new opportunities for comparative morphological analyses over time and between species.

Genetic Underpinnings of Host Manipulation by Ophiocordyceps as Revealed by Comparative Transcriptomics

Ant-infecting Ophiocordyceps fungi are globally distributed, host manipulating, specialist parasites that drive aberrant behaviors in infected ants, at a lethal cost to the host. An apparent increase in activity and wandering behaviors precedes a final summiting and biting behavior onto vegetation, which positions the manipulated ant in a site beneficial for fungal growth and transmission. We investigated the genetic underpinnings of host manipulation by: (i) producing a high-quality hybrid assembly and annotation of the Ophiocordyceps camponoti-floridani genome, (ii) conducting laboratory infections coupled with RNAseq of O. camponoti-floridani and its host, Camponotus floridanus, and (iii) comparing these data to RNAseq data of Ophiocordyceps kimflemingiae and Camponotus castaneus as a powerful method to identify gene expression patterns that suggest shared behavioral manipulation mechanisms across Ophiocordyceps-ant species interactions. We propose differentially expressed genes tied to ant neurobiology, odor response, circadian rhythms, and foraging behavior may result by activity of putative fungal effectors such as enterotoxins, aflatrem, and mechanisms disrupting feeding behaviors in the ant.

Assessment of vector-host-pathogen relationships using data mining and machine learning

Infectious diseases, including vector-borne diseases transmitted by arthropods, are a leading cause of morbidity and mortality worldwide. In the era of big data, addressing broad-scale, fundamental questions regarding the complex dynamics of these diseases will increasingly require the integration of diverse datasets to produce new biological knowledge. This review provides a current snapshot of the systematic assessment of the relationships between microbial pathogens, arthropod vectors and mammalian hosts using data mining and machine learning. We employ PRISMA to identify 32 key papers relevant to this topic. Our analysis shows an increasing use of data mining and machine learning tasks and techniques, including prediction, classification, clustering, association rules mining, and deep learning, over the last decade. However, it also reveals a number of critical challenges in applying these to the study of vector-host-pathogen interactions at various systems biology levels. Here, relevant studies, current limitations and future directions are discussed. Furthermore, the quality of data in relevant papers was assessed using the FAIR (Findable, Accessible, Interoperable, Reusable) compliance criteria to evaluate and encourage reproducibility and shareability of research outcomes. Although shortcomings in their application remain, data mining and machine learning have significant potential to break new ground in understanding fundamental aspects of vector-host-pathogen relationships and their application in this field should be encouraged. In particular, while predictive modeling, feature engineering and supervised machine learning are already being used in the field, other data mining and machine learning methods such as deep learning and association rules analysis lag behind and should be implemented in combination with established methods to accelerate hypothesis and knowledge generation in the domain.

Application of deep learning methods in biological networks

The increase in biological data and the formation of various biomolecule interaction databases enable us to obtain diverse biological networks. These biological networks provide a wealth of raw materials for further understanding of biological systems, the discovery of complex diseases and the search for therapeutic drugs. However, the increase in data also increases the difficulty of biological networks analysis. Therefore, algorithms that can handle large, heterogeneous and complex data are needed to better analyze the data of these network structures and mine their useful information. Deep learning is a branch of machine learning that extracts more abstract features from a larger set of training data. Through the establishment of an artificial neural network with a network hierarchy structure, deep learning can extract and screen the input information layer by layer and has representation learning ability. The improved deep learning algorithm can be used to process complex and heterogeneous graph data structures and is increasingly being applied to the mining of network data information. In this paper, we first introduce the used network data deep learning models. After words, we summarize the application of deep learning on biological networks. Finally, we discuss the future development prospects of this field.

Enabling community-based metrology for wood-degrading fungi

BACKGROUND

Lignocellulosic biomass could support a greatly-expanded bioeconomy. Current strategies for using biomass typically rely on single-cell organisms and extensive ancillary equipment to produce precursors for downstream manufacturing processes. Alternative forms of bioproduction based on solid-state fermentation and wood-degrading fungi could enable more direct means of manufacture. However, basic methods for cultivating wood-degrading fungi are often ad hoc and not readily reproducible. Here, we developed standard reference strains, substrates, measurements, and methods sufficient to begin to enable reliable reuse of mycological materials and products in simple laboratory settings.

RESULTS

We show that a widely-available and globally-regularized consumer product (Pringles™) can support the growth of wood-degrading fungi, and that growth on Pringles™-broth can be correlated with growth on media made from a fully-traceable and compositionally characterized substrate (National Institute of Standards and Technology Reference Material 8492 Eastern Cottonwood Whole Biomass Feedstock). We also establish a Relative Extension Unit (REU) framework that is designed to reduce variation in quantification of radial growth measurements. So enabled, we demonstrate that five laboratories were able to compare measurements of wood-fungus performance via a simple radial extension growth rate assay, and that our REU-based approach reduced variation in reported measurements by up to ~ 75%.

CONCLUSIONS

Reliable reuse of materials, measures, and methods is necessary to enable distributed bioproduction processes that can be adopted at all scales, from local to industrial. Our community-based measurement methods incentivize practitioners to coordinate the reuse of standard materials, methods, strains, and to share information supporting work with wood-degrading fungi.

The metabolic alteration and apparent preservation of the zombie ant brain

Some parasites can manipulate the behavior of their animal hosts to increase transmission. An interesting area of research is understanding how host neurobiology is manipulated by microbes to the point of displaying such aberrant behaviors. Here, we characterize the metabolic profile of the brain of an insect at the moment of the behavioral manipulation by a parasitic microbe. Our model system are ants infected with the parasitic fungus Ophiocordyceps kimflemingiae (=unilateralis), which manipulates ants to climb and bite into plant substrates, before killing the host (i.e. zombie ants). At the moment of the behavioral manipulation by the fungus, the host's brain is not invaded by the fungus which is known to extensively invade muscle tissue. We found that, despite not being invaded by the parasite, the brains of manipulated ants are notably different, showing alterations in neuromodulatory substances, signs of neurodegeneration, changes in energy use, and antioxidant compound that signal stress reactions by the host. Ergothionine, a fungal derived compound with known neuronal cytoprotection functions was found to be highly elevated in zombie ant brains suggesting the fungus, which does not invade the central nervous system, is preserving the brain.

Zombie ant death grip due to hypercontracted mandibular muscles

There are numerous examples of parasites that manipulate the behavior of the hosts that they infect. One such host-pathogen relationship occurs between the 'zombie-ant fungus' Ophiocordyceps unilateralis sensu lato and its carpenter ant host. Infected ants climb to elevated locations and bite onto vegetation where they remain permanently affixed well after death. The mandibular muscles, but not the brain, of infected ants are extensively colonized by the fungus. We sought to investigate the mechanisms by which O. unilateralis s.l. may be able to influence mandibular muscle contraction despite widespread muscle damage. We found that infected muscles show evidence of hypercontraction. Despite the extensive colonization, both motor neurons and neuromuscular junctions appear to be maintained. Infection results in sarcolemmal damage, but this is not specific to the death grip. We found evidence of precise penetration of muscles by fungal structures and the presence of extracellular vesicle-like particles, both of which may contribute to mandibular hypercontraction.

Deep learning-based selection of human sperm with high DNA integrity

Despite the importance of sperm DNA to human reproduction, currently no method exists to assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled clinicians select sperm based on a variety of morphological and motility criteria, but without direct knowledge of their DNA cargo. Here, we show how a deep convolutional neural network can be trained on a collection of ~1000 sperm cells of known DNA quality, to predict DNA quality from brightfield images alone. Our results demonstrate moderate correlation (bivariate correlation ~0.43) between a sperm cell image and DNA quality and the ability to identify higher DNA integrity cells relative to the median. This deep learning selection process is directly compatible with current, manual microscopy-based sperm selection and could assist clinicians, by providing rapid DNA quality predictions (under 10 ms per cell) and sperm selection within the 86th percentile from a given sample.

Psychoactive plant- and mushroom-associated alkaloids from two behavior modifying cicada pathogens

Entomopathogenic fungi routinely kill their hosts before releasing infectious spores, but a few species keep insects alive while sporulating, which enhances dispersal. Transcriptomics- and metabolomics-based studies of entomopathogens with post-mortem dissemination from their parasitized hosts have unraveled infection processes and host responses. However, the mechanisms underlying active spore transmission by Entomophthoralean fungi in living insects remain elusive. Here we report the discovery, through metabolomics, of the plant-associated amphetamine, cathinone, in four Massospora cicadina-infected periodical cicada populations, and the mushroom-associated tryptamine, psilocybin, in annual cicadas infected with Massospora platypediae or Massospora levispora, which likely represent a single fungal species. The absence of some fungal enzymes necessary for cathinone and psilocybin biosynthesis along with the inability to detect intermediate metabolites or gene orthologs are consistent with possibly novel biosynthesis pathways in Massospora. The neurogenic activities of these compounds suggest the extended phenotype of Massospora that modifies cicada behavior to maximize dissemination is chemically-induced.

Ophiocordyceps-ant interactions as an integrative model to understand the molecular basis of parasitic behavioral manipulation

Ophiocordyceps-infected ants display a substrate biting behavior that aids parasite transmission. World-wide research into this behavioral manipulation has led to new fungal species descriptions, annotated genomes, and detailed field observations. Experimentally tractable modified ant behaviors and the development of infection techniques have enabled the quest for the molecular basis of this phenomenon. Behavioral studies followed by transcriptomics, metabolomics and three-dimensional electron microscopy have led to novel mechanistic hypotheses. This multidisciplinary work represents a big leap forward. However, definitive answers have yet to be obtained. A comprehensive understanding hinges on continued integrative efforts that reveal the precise natural history, behavioral ecology and evolutionary relationships between Ophiocordyceps-ant systems, and the true functions and involvement of genes and metabolites in behavioral manipulation.

The evolutionary ecology of circadian rhythms in infection

Biological rhythms coordinate organisms' activities with daily rhythms in the environment. For parasites, this includes rhythms in both the external abiotic environment and the within-host biotic environment. Hosts exhibit rhythms in behaviours and physiologies, including immune responses, and parasites exhibit rhythms in traits underpinning virulence and transmission. Yet, the evolutionary and ecological drivers of rhythms in traits underpinning host defence and parasite offence are largely unknown. Here, we explore how hosts use rhythms to defend against infection, why parasites have rhythms and whether parasites can manipulate host clocks to their own ends. Harnessing host rhythms or disrupting parasite rhythms could be exploited for clinical benefit; we propose an interdisciplinary effort to drive this emerging field forward.

Investigation of Polymer Coatings Formed by Polyvinyl Alcohol and Silver Nanoparticles on Copper Surface in Acid Medium by Means of Deep Convolutional Neural Networks

In order to assemble effective protective coatings against corrosion, electrochemical techniques such as linear potentiometry and cyclic voltammetry were performed on a copper surface in 0.1 mol·L−1 HCl solution containing 0.1% polyvinyl alcohol (PVA) in the absence and presence of silver nanoparticles (nAg/PVA). A recent paradigm was used to distinguish the features of the coatings, that is, a deep convolutional neural network (CNN) was implemented to automatically and hierarchically extract the discriminative characteristics from the information given by optical microscopy images. In our study, the material surface morphology, controlled by the CNN without the interference of the human factor, was successfully conducted to extract the similarities/differences between unprotected and protected surfaces in order to establish the PVA and nAg/PVA performance to retard copper corrosion. The CNN results were confirmed by the classical investigation of copper behavior in hydrochloric acid solution in the absence and presence of polyvinyl alcohol and silver nanoparticles. The electrochemical measurements showed that the corrosion current density (icorr) decreased and polarization resistance (Rp) increased, with both PVA and nAg/PVA being effective inhibitors for copper corrosion in an acid environment, forming polymer protective coatings by adsorption on the metal surface. Furthermore, scanning electron microscopy (SEM) certifies the formation of polymer coatings, revealing a specific morphology of the copper surface in the presence of PVA and nAg/PVA, very different from that of corroded copper in uninhibited solutions. Finally, the correlation of the CNN information with experimental data was reported.

Biological evolution as defense of 'self'

Although the origin of self-referential consciousness is unknown, it can be argued that the instantiation of self-reference was the commencement of the living state as phenomenal experientiality. As self-referential cognition is demonstrated by all living organisms, life can be equated with the sustenance of cellular homeostasis in the continuous defense of 'self'. It is proposed that the epicenter of 'self' is perpetually embodied within the basic cellular form in which it was instantiated. Cognition-Based Evolution argues that all of biological and evolutionary development represents the perpetual autopoietic defense of self-referential basal cellular states of homeostatic preference. The means by which these states are attained and maintained is through self-referential measurement of information and its communication. The multicellular forms, either as biofilms or holobionts, represent the cellular attempt to achieve maximum states of informational distinction and energy efficiency through individual and collective means. In this frame, consciousness, self-consciousness and intelligence can be identified as forms of collective cellular phenotype directed towards the defense of fundamental cellular self-reference.

Three-Dimensional Portable Document Format (3D PDF) in Clinical Communication and Biomedical Sciences: Systematic Review of Applications, Tools, and Protocols

Background

The Portable Document Format (PDF) is the standard file format for the communication of biomedical information via the internet and for electronic scholarly publishing. Although PDF allows for the embedding of three-dimensional (3D) objects and although this technology has great potential for the communication of such data, it is not broadly used by the scientific community or by clinicians.

Objective

The objective of this review was to provide an overview of existing publications that apply 3D PDF technology and the protocols and tools for the creation of model files and 3D PDFs for scholarly purposes to demonstrate the possibilities and the ways to use this technology.

Methods

A systematic literature review was performed using PubMed and Google Scholar. Articles searched for were in English, peer-reviewed with biomedical reference, published since 2005 in a journal or presented at a conference or scientific meeting. Ineligible articles were removed after screening. The found literature was categorized into articles that (1) applied 3D PDF for visualization, (2) showed ways to use 3D PDF, and (3) provided tools or protocols for the creation of 3D PDFs or necessary models. Finally, the latter category was analyzed in detail to provide an overview of the state of the art.

Results

The search retrieved a total of 902 items. Screening identified 200 in-scope publications, 13 covering the use of 3D PDF for medical purposes. Only one article described a clinical routine use case; all others were pure research articles. The disciplines that were covered beside medicine were many. In most cases, either animal or human anatomies were visualized. A method, protocol, software, library, or other tool for the creation of 3D PDFs or model files was described in 19 articles. Most of these tools required advanced programming skills and/or the installation of further software packages. Only one software application presented an all-in-one solution with a graphical user interface.

Conclusions

The use of 3D PDF for visualization purposes in clinical communication and in biomedical publications is still not in common use, although both the necessary technique and suitable tools are available, and there are many arguments in favor of this technique. The potential of 3D PDF usage should be disseminated in the clinical and biomedical community. Furthermore, easy-to-use, standalone, and free-of-charge software tools for the creation of 3D PDFs should be developed.

Robust manipulation of the behavior of Drosophila melanogaster by a fungal pathogen in the laboratory

Many microbes induce striking behavioral changes in their animal hosts, but how they achieve this is poorly understood, especially at the molecular level. Mechanistic understanding has been largely constrained by the lack of an experimental system amenable to molecular manipulation. We recently discovered a strain of the behavior-manipulating fungal pathogen Entomophthora muscae infecting wild Drosophila, and established methods to infect D. melanogaster in the lab. Lab-infected flies manifest the moribund behaviors characteristic of E. muscae infection: hours before death, they climb upward, extend their proboscides, affixing in place, then raise their wings, clearing a path for infectious spores to launch from their abdomens. We found that E. muscae invades the nervous system, suggesting a direct means by which the fungus could induce behavioral changes. Given the vast molecular toolkit available for D. melanogaster, we believe this new system will enable rapid progress in understanding how E. muscae manipulates host behavior.

Insights into the Temporal Gene Expression Pattern in Lymantria dispar Larvae During the Baculovirus Induced Hyperactive Stage

Baculoviruses are effective biological control agents for many insect pests. They not only efficiently challenge the host immune system but also make them hyperactive for better virus dispersal. Some investigations have focused on the viral mechanisms for induction of such altered response from the host. However, there are no current studies monitoring changes in gene expression during this altered phenotype in infected larvae. The L. dispar multiple nucleopolyhedrovirus (LdMNPV) induces hyperactivity in third instar L. dispar larvae at 3-days post infection (dpi), to continued till 6 dpi. The transcriptome profiles of the infected and uninfected larvae at these time points were analyzed to provide new clues on the response of the larvae towards infection during hyperactivity. Gene ontology enrichment analysis revealed, most of the differentially expressed genes (DEGs) were involved in proteolysis, extracellular region, and serine-type endopeptidase activity. Similarly, Kyoto Encyclopedia of Genes and Genome enrichment analysis showed maximum enrichment of 487 genes of the signal transduction category and neuroactive ligand-receptor interaction sub-category with 85 annotated genes. In addition, enrichment map visualization of gene set enrichment analysis showed the coordinated response of neuroactive ligand-receptor interaction genes with other functional gene sets, as an important signal transduction mechanism during the hyperactive stage. Interestingly all the DEGs in neuroactive ligand-receptor interactions were serine proteases, their differential expression during the hyperactive stage correlated with their conceivable involvement in disease progression and the resulting altered phenotype during this period. The outcome provides a basic understanding of L. dispar larval responses to LdMNPV infection during the hyperactive stage and helps to determine the important host factors involved in this process.

3D virtual histology at the host/parasite interface: visualisation of the master manipulator, Dicrocoelium dendriticum, in the brain of its ant host

Some parasites are able to manipulate the behaviour of their hosts to their own advantage. One of the most well-established textbook examples of host manipulation is that of the trematode Dicrocoelium dendriticum on ants, its second intermediate host. Infected ants harbour encysted metacercariae in the gaster and a non-encysted metacercaria in the suboesophageal ganglion (SOG); however, the mechanisms that D. dendriticum uses to manipulate the ant behaviour remain unknown, partly because of a lack of a proper and direct visualisation of the physical interface between the parasite and the ant brain tissue. Here we provide new insights into the potential mechanisms that this iconic manipulator uses to alter its host's behaviour by characterising the interface between D. dendriticum and the ant tissues with the use of non-invasive micro-CT scanning. For the first time, we show that there is a physical contact between the parasite and the ant brain tissue at the anteriormost part of the SOG, including in a case of multiple brain infection where only the parasite lodged in the most anterior part of the SOG was in contact with the ant brain tissue. We demonstrate the potential of micro-CT to further understand other parasite/host systems in parasitological research.

Comparative Genomics Reveals the Core Gene Toolbox for the Fungus-Insect Symbiosis

Modern genomics has shed light on many entomopathogenic fungi and expanded our knowledge widely; however, little is known about the genomic features of the insect-commensal fungi. Harpellales are obligate commensals living in the digestive tracts of disease-bearing insects (black flies, midges, and mosquitoes). In this study, we produced and annotated whole-genome sequences of nine Harpellales taxa and conducted the first comparative analyses to infer the genomic diversity within the members of the Harpellales. The genomes of the insect gut fungi feature low (26% to 37%) GC content and large genome size variations (25 to 102 Mb). Further comparisons with insect-pathogenic fungi (from both Ascomycota and Zoopagomycota), as well as with free-living relatives (as negative controls), helped to identify a gene toolbox that is essential to the fungus-insect symbiosis. The results not only narrow the genomic scope of fungus-insect interactions from several thousands to eight core players but also distinguish host invasion strategies employed by insect pathogens and commensals. The genomic content suggests that insect commensal fungi rely mostly on adhesion protein anchors that target digestive system, while entomopathogenic fungi have higher numbers of transmembrane helices, signal peptides, and pathogen-host interaction (PHI) genes across the whole genome and enrich genes as well as functional domains to inactivate the host inflammation system and suppress the host defense. Phylogenomic analyses have revealed that genome sizes of Harpellales fungi vary among lineages with an integer-multiple pattern, which implies that ancient genome duplications may have occurred within the gut of insects.

Insect guts harbor various microbes that are important for host digestion, immune response, and disease dispersal in certain cases. Bacteria, which are among the primary endosymbionts, have been studied extensively. However, fungi, which are also frequently encountered, are poorly known with respect to their biology within the insect guts. To understand the genomic features and related biology, we produced the whole-genome sequences of nine gut commensal fungi from disease-bearing insects (black flies, midges, and mosquitoes). The results show that insect gut fungi tend to have low GC content across their genomes. By comparing these commensals with entomopathogenic and free-living fungi that have available genome sequences, we found a universal core gene toolbox that is unique and thus potentially important for the insect-fungus symbiosis. This comparative work also uncovered different host invasion strategies employed by insect pathogens and commensals, as well as a model system to study ancient fungal genome duplication within the gut of insects.