Reconstructing heterogeneous pathogen interactions from co-occurrence data via statistical network inference

Infectious diseases often involve multiple pathogen species or multiple strains of the same pathogen. As such, knowledge of how different pathogen species or pathogen strains interact is key to understand and predict the outcome of interventions that target only a single pathogen or subset of strains involved in disease. While population-level data have been used to infer pathogen strain interactions, most previously used inference methods only consider uniform interactions between all strains, or focus on marginal interactions between pairs of strains (without correction for indirect interactions through other strains). Here, we evaluate whether statistical network inference could be useful for reconstructing heterogeneous interaction networks from cross-sectional surveys tracking co-occurrence of multi-strain pathogens. To this end, we applied a suite of network models to data simulating endemic infection states of pathogen strains. Satisfactory performance was demonstrated by unbiased estimation of interaction parameters for large sample size. Accurate reconstruction of networks may require regularization or penalizing for sample size. Of note, performance deteriorated in the presence of host heterogeneity, but this could be overcome by correcting for individual-level risk factors. Our work demonstrates how statistical network inference could prove useful for detecting pathogen interactions and may have implications beyond epidemiology.

Digitalization of Clubroot Disease Index, a Long Overdue Task

Clubroot is a devastating disease caused by the protist Plasmodiophora brassicae Woronin. After root hair colonization, the clubroot pathogen induces clubs that block water uptake, leading to dehydration and death. The study of the severity of plant diseases is very important. It allows us to characterize the level of resistance of plant germplasm and to classify the virulence of pathogen strains or isolates. Lately, the use of learning machines and automatization has expanded to plant pathology. Fast, reliable and unbiased methods are always necessary, and with clubroot disease indexing this is not different. From this perspective, we discuss why this is the case and how we could achieve this long overdue task for clubroot disease.

Host Specialisation, Immune Cross-Reaction and the Composition of Communities of Co-circulating Borrelia Strains

We use mathematical modelling to examine how microbial strain communities are structured by the host specialisation traits and antigenic relationships of their members. The model is quite general and broadly applicable, but we focus on Borrelia burgdorferi, the Lyme disease bacterium, transmitted by ticks to mice and birds. In this system, host specialisation driven by the evasion of innate immunity has been linked to multiple niche polymorphism, while antigenic differentiation driven by the evasion of adaptive immunity has been linked to negative frequency dependence. Our model is composed of two host species, one vector, and multiple co-circulating pathogen strains that vary in their host specificity and their antigenic distances from one another. We explore the conditions required to maintain pathogen diversity. We show that the combination of host specificity and antigenic differentiation creates an intricate niche structure. Unequivocal rules that relate the stability of a strain community directly to the trait composition of its members are elusive. However, broad patterns are evident. When antigenic differentiation is weak, stable communities are typically composed entirely of generalists that can exploit either host species equally well. As antigenic differentiation increases, more diverse stable communities emerge, typically around trait compositions of generalists, generalists and very similar specialists, and specialists roughly balanced between the two host species.

Competition between strains of Borrelia afzelii in the host tissues and consequences for transmission to ticks

Pathogen species often consist of genetically distinct strains, which can establish mixed infections or coinfections in the host. In coinfections, interactions between pathogen strains can have important consequences for their transmission success. We used the tick-borne bacterium Borrelia afzelii, which is the most common cause of Lyme disease in Europe, as a model multi-strain pathogen to investigate the relationship between coinfection, competition between strains, and strain-specific transmission success. Mus musculus mice were infected with one or two strains of B. afzelii, strain transmission success was measured by feeding ticks on mice, and the distribution of each strain in six different mouse organs and the ticks was measured using qPCR. Coinfection and competition reduced the tissue infection prevalence of both strains and changed their bacterial abundance in some tissues. Coinfection and competition also reduced the transmission success of the B. afzelii strains from the infected hosts to feeding ticks. The ability of the B. afzelii strains to establish infection in the host tissues was strongly correlated with their transmission success to the tick vector. Our study demonstrates that coinfection and competition between pathogen strains inside the host tissues can have major consequences for their transmission success.

Complete and Circularized Genome Assembly of a Human Isolate of Vibrio navarrensis Biotype pommerensis with MiSeq and MinION Sequence Data

ABSTRACT Vibrio navarrensis is a rare human pathogen. Strains of Vibrio navarrensis biotype pommerensis were isolated from seawater of the Baltic Sea. Recently, a strain of this biotype was recovered from a human patient. The isolate contains two circular chromosomes and a large plasmid with a size of 180 kb.

Fructose and Trehalose Selectively Enhance In Vitro Sporulation of Paenibacillus larvae ERIC I and ERIC II Strains

Paenibacillus larvae is a Gram-positive bacterium, the spores of which are the causative agent of the most destructive brood disease of honeybees, American foulbrood (AFB). Obtaining viable spores of pathogen strains is requisite for different studies concerning AFB. The aim of this work was to investigate the effects of five saccharides that may naturally occur in higher amounts in bee larvae on in vitro sporulation of P. larvae. The effect of individual saccharides at different concentrations on spore yields of P. larvae strains of epidemiologically important ERIC genotypes was examined in Columbia sheep blood agar (CSA) and MYPGP agar media. It was found that fructose in ERIC I and trehalose in ERIC II strains at concentrations in the range of 0.5–2% represent new sporulation factors that significantly enhanced the yields of viable spores in both media, mostly in a concentration-dependent manner. The enhancements in spore yield were mainly caused by improvements of the germination ability of the spores produced. Glucose, maltose and sucrose at 1% or 0.5% concentrations also supported sporulation but to a lower extent and not in all strains and media. Based on the knowledge gained, a novel procedure was proposed for the preparation of viable P. larvae spores with supposed improved quality for AFB research.

Stacking Resistance Genes in Multiparental Interspecific Potato Hybrids to Anticipate Late Blight Outbreaks

Stacking (pyramiding) several resistance genes of diverse race specificity in one and the same plant by hybridization provides for high and durable resistance to major diseases, such as potato late blight (LB), especially when breeders combine highly efficient genes for broad-spectrum resistance that are novel to the intruding pathogens. Our collection of potato hybrids manifesting long-lasting LB resistance comprises, as a whole, the germplasm of 26 or 22 Solanum species (as treated by Bukasov and Hawkes, respectively), with up to 8–9 species listed in the pedigree of an individual hybrid. This collection was screened with the markers of ten genes for race-specific resistance to Phytophthora infestans (Rpi genes) initially identified in S. demissum (R1, R2, R3a, R3b, and R8), S. bulbocastanum/S. stoloniferum (Rpi-blb1/ Rpi-sto1, Rpi-blb2, Rpi-blb3) and S. venturii (Rpi-vnt1). The hybrids comprised the markers for up to four-six Rpi genes per plant, and the number of markers was significantly related to LB resistance. Nevertheless, a considerable portion of resistance apparently depended on presently insufficiently characterized resistance genes. Bred from these multiparental hybrids, the advanced lines with the stacks of broad-specificity Rpi genes will help anticipate LB outbreaks caused by rapid pathogen evolution and the arrival of new pathogen strains.

Inter-stain interactions of a vector-borne parasite over its life cycle, "Borrelia afzelii", "Mus musculus", "Ixodes ricinus" model

Many pathogens consist of genetically distinct strains. When hosts are simultaneously infected with multiple strains the phenomenon is known as a mixed infection or a co-infection. In mixed infections, strains can interact with each other and these interactions between strains can have important consequences for their transmission and frequency in the pathogen population. Vector-borne pathogens have a complex life cycle that includes both a vertebrate host and an arthropod vector. As a result of this complexity, interactions between strains can occur in both the host and the vector. Interactions between strains in the vertebrate host are expected to influence transmission from the co-infected host to uninfected vectors. Conversely, interactions between strains in the arthropod vector are expected to influence transmission from the co-infected vector to the uninfected host. This thesis used the tick-borne bacterium, Borrelia afzelii, as a model system to investigate how co-infection and interactions between strains influence their transmission and lifetime fitness over the course of the tick-borne life cycle. B. afzelii is a common cause of Lyme disease in Europe, it is transmitted by the castor bean tick (Ixodes ricinus) and it uses small mammals (e.g. rodents) as a reservoir host. An experimental approach with two genetically distinct strains of B. afzelii (one Swiss stain, one Finnish strain) was used to investigate the effects of co-infection in both the host and the vector. In Chapter 1, lab mice were experimentally infected via tick bite with either 1 or 2 strains of B. afzelii. The infected mice were then fed upon by I. ricinus ticks from a laboratory colony to quantify host-to-tick transmission. qPCR was used to determine the presence and abundance of each strain in the ticks. Chapter 1 found that co-infection in the mice reduced the host-to-tick transmission success of the strains. This chapter also found that co-infection reduced the abundance of each strain in the tick. This is one of the first studies to show that co-infection is important for determining the abundance of the pathogen strains in the vector. In the lifecycle of B. afzelii, the bacterium is acquired by larval ticks that blood feed on an infected host. These larvae subsequently moult into nymphs that are responsible for transmitting the bacterium to the next generation of hosts. The bacterium has to persist inside the midgut of the nymph for a long time (8 – 12 months). Chapter 2 investigated whether nymphal ageing (1-month-old vs 4-month-old nymphs) under different environmental conditions (summer vs winter) influenced the interactions between strains in co-infected ticks. The spirochete abundance inside the nymph decreased with nymphal age, but there was no effect of the environmental conditions investigated. In Chapter 3, the presence and abundance of the two strains of B. afzelii were quantified in the tissues of 6 different organs (bladder, left ear, right ear, heart, ankle joint, and dorsal skin) that were harvested from the co-infected and singly infected mice. This study showed that co-infection in the mouse host reduced the prevalence of the Finnish strain in the host tissues (but the Swiss strain was not affected by co-infection). Chapter 3 found a positive relationship between the prevalence (or abundance) of each strain in the mouse tissues and the host-to-tick transmission of each strain. External tissues (e.g. ears) were more important for host-to-tick transmission than internal organs (e.g. bladder). Chapter 3 enhances our understanding of the biology of mixed infections by showing the causal links between co-infection in the host, the distribution and abundance of the strains in host tissues and the subsequent host-to-tick transmission success of the strains. Chapter 4 investigated how co-infection in the arthropod vector influences vector-to-host transmission success. A second infection experiment was performed, where naïve mice were exposed to nymphs that were either co-infected or infected with one of the two strains (i.e., using the nymphs generated in Chapters 1 and 2). The infection status of the mice was then tested using the same qPCR-based methods. Importantly, Chapter 4 confirmed that the negative effect of co-infection in the mouse on host-to-tick transmission (observed in Chapters 1, 2, and 3) had real fitness consequences for subsequent tick-to-host transmission. Ticks that had fed on co-infected mice were much less likely to transmit their strains to the host because these strains were less common inside these co-infected ticks. Chapter 4 did not find evidence that co-infection in the nymph influenced the nymph-to-host transmission success of each strain. This Chapter did find that there was a two-fold difference in nymph-to-host transmission success between the two strains. This work provides evidence for the idea that vector-borne pathogen strains can exhibit trade-offs across the different steps of their complex life cycles. In the co-infected mice, the Swiss strain had higher host-to-tick transmission success than the Finnish strain. Conversely, the Finnish strains had higher spirochete loads in the tick vector and had tick-to-host transmission success. Thus, the Swiss and Finnish strains are specialized on the host versus the vector, respectively.

When might Host Heterogeneity Drive the Evolution of Asymptomatic, Pandemic Coronaviruses?

For most emerging infectious diseases, including SARS-Coronavirus-2 (SARS-CoV-2), pharmaceutical intervensions such as drugs and vaccines are not available, and disease surveillance followed by isolating, contact-tracing and quarantining infectious individuals is critical for controlling outbreaks. These interventions often begin by identifying symptomatic individuals. However, by actively removing pathogen strains likely to be symptomatic, such interventions may inadvertently select for strains less likely to result in symptomatic infections. Additionally, the pathogen's fitness landscape is structured around a heterogeneous host pool. In particular, uneven surveillance efforts and distinct transmission risks across host classes can drastically alter selection pressures. Here we explore this interplay between evolution caused by disease control efforts, on the one hand, and host heterogeneity in the efficacy of public health interventions on the other, on the potential for a less symptomatic, but widespread, pathogen to evolve. We use an evolutionary epidemiology model parameterized for SARS-CoV-2, as the widespread potential for silent transmission by asymptomatic hosts has been hypothesized to account, in part, for its rapid global spread. We show that relying on symptoms-driven reporting for disease control ultimately shifts the pathogen's fitness landscape and can cause pandemics. We find such outcomes result when isolation and quarantine efforts are intense, but insufficient for suppression. We further show that when host removal depends on the prevalence of symptomatic infections, intense isolation efforts can select for the emergence and extensive spread of more asymptomatic strains. The severity of selection pressure on pathogens caused by these interventions likely lies somewhere between the extremes of no intervention and thoroughly successful eradication. Identifying the levels of public health responses that facilitate selection for asymptomatic pathogen strains is therefore critical for calibrating disease suppression and surveillance efforts and for sustainably managing emerging infectious diseases.