Epigenomic Landscape of Lyme Disease Spirochetes Reveals Novel Motifs

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

BACKGROUND

Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals, and accurate laboratory testing and interpretation for clinical diagnosis validation. A lack of these can lead to delayed diagnosis and treatment, which can exacerbate the severity of Lyme disease symptoms. Therefore, there is a need to improve the monitoring of Lyme disease by using other data sources, such as web-based data.

OBJECTIVE

We analyzed global Twitter data to understand its potential and limitations as a tool for Lyme disease surveillance. We propose a transformer-based classification system to identify potential Lyme disease cases using self-reported tweets.

METHODS

Our initial sample included 20,000 tweets collected worldwide from a database of over 1.3 million Lyme disease tweets. After preprocessing and geolocating tweets, tweets in a subset of the initial sample were manually labeled as potential Lyme disease cases or non-Lyme disease cases using carefully selected keywords. Emojis were converted to sentiment words, which were then replaced in the tweets. This labeled tweet set was used for the training, validation, and performance testing of DistilBERT (distilled version of BERT [Bidirectional Encoder Representations from Transformers]), ALBERT (A Lite BERT), and BERTweet (BERT for English Tweets) classifiers.

RESULTS

The empirical results showed that BERTweet was the best classifier among all evaluated models (average F1-score of 89.3%, classification accuracy of 90.0%, and precision of 97.1%). However, for recall, term frequency-inverse document frequency and k-nearest neighbors performed better (93.2% and 82.6%, respectively). On using emojis to enrich the tweet embeddings, BERTweet had an increased recall (8% increase), DistilBERT had an increased F1-score of 93.8% (4% increase) and classification accuracy of 94.1% (4% increase), and ALBERT had an increased F1-score of 93.1% (5% increase) and classification accuracy of 93.9% (5% increase). The general awareness of Lyme disease was high in the United States, the United Kingdom, Australia, and Canada, with self-reported potential cases of Lyme disease from these countries accounting for around 50% (9939/20,000) of the collected English-language tweets, whereas Lyme disease-related tweets were rare in countries from Africa and Asia. The most reported Lyme disease-related symptoms in the data were rash, fatigue, fever, and arthritis, while symptoms, such as lymphadenopathy, palpitations, swollen lymph nodes, neck stiffness, and arrythmia, were uncommon, in accordance with Lyme disease symptom frequency.

CONCLUSIONS

The study highlights the robustness of BERTweet and DistilBERT as classifiers for potential cases of Lyme disease from self-reported data. The results demonstrated that emojis are effective for enrichment, thereby improving the accuracy of tweet embeddings and the performance of classifiers. Specifically, emojis reflecting sadness, empathy, and encouragement can reduce false negatives.

Endogenous Linear Plasmids lp28-4 and lp25 Are Required for Infectivity and Restriction Protection in the Lyme Disease Spirochete Borrelia mayonii

Borrelia mayonii is a newly recognized causative agent of Lyme disease in the Upper Midwestern United States, with distinct clinical presentations compared to classical Lyme disease caused by other Lyme Borrelia species. However, little is known about the B. mayonii genetic determinants required for establishing infection or perpetuating disease in mammals. Extrachromosomal plasmids in Borrelia species often encode proteins necessary for infection and pathogenesis, and spontaneous loss of these plasmids can lead to the identification of virulence determinant genes. Here, we describe infection of Lyme disease-susceptible C3H mice with B. mayonii, and show bacterial dissemination and persistence in peripheral tissues. Loss of endogenous plasmids, including lp28-4, lp25, and lp36 correlated with reduced infectivity in mice. The apparent requirement for lp28-4 during murine infection suggests the presence of a novel virulence determinant, as this plasmid does not encode homologs of any known virulence determinant. We also describe transformation and stable maintenance of a self-replicating shuttle vector in B. mayonii, and show that loss of either lp25 or lp28-4 correlated with increased transformation competency. Finally, we demonstrate that linear plasmids lp25 and lp28-4 each encode functional restriction modification systems with distinct but partially overlapping target modification sequences, which likely accounts for the observed decrease in transformation efficiency when those plasmids are present. Taken together, this study describes a role for endogenous plasmids in mammalian infection and restriction protection in the Lyme disease spirochete Borrelia mayonii.

Coupled induction of prophage and virulence factors during tick transmission of the Lyme disease spirochete

The alternative sigma factor RpoS plays a central role in the critical host-adaptive response of the Lyme disease spirochete, Borrelia burgdorferi. We previously identified bbd18 as a negative regulator of RpoS but could not inactivate bbd18 in wild-type spirochetes. In the current study we employed an inducible bbd18 gene to demonstrate the essential nature of BBD18 for viability of wild-type spirochetes in vitro and at a unique point in vivo. Transcriptomic analyses of BBD18-depleted cells demonstrated global induction of RpoS-dependent genes prior to lysis, with the absolute requirement for BBD18, both in vitro and in vivo, circumvented by deletion of rpoS. The increased expression of plasmid prophage genes and the presence of phage particles in the supernatants of lysing cultures indicate that RpoS regulates phage lysis-lysogeny decisions. Through this work we identify a mechanistic link between endogenous prophages and the RpoS-dependent adaptive response of the Lyme disease spirochete.

Phylogenomic Diversity Elucidates Mechanistic Insights into Lyme Borreliae-Host Association

Host association-the selective adaptation of pathogens to specific host species-evolves through constant interactions between host and pathogens, leaving a lot yet to be discovered on immunological mechanisms and genomic determinants. The causative agents of Lyme disease (LD) are spirochete bacteria composed of multiple species of the Borrelia burgdorferi sensu lato complex, including B. burgdorferi (Bb), the main LD pathogen in North America-a useful model for the study of mechanisms underlying host-pathogen association. Host adaptation requires pathogens' ability to evade host immune responses, such as complement, the first-line innate immune defense mechanism. We tested the hypothesis that different host-adapted phenotypes among Bb strains are linked to polymorphic loci that confer complement evasion traits in a host-specific manner. We first examined the survivability of 20 Bb strains in sera in vitro and/or bloodstream and tissues in vivo from rodent and avian LD models. Three groups of complement-dependent host-association phenotypes emerged. We analyzed complement-evasion genes, identified a priori among all strains and sequenced and compared genomes for individual strains representing each phenotype. The evolutionary history of ospC loci is correlated with host-specific complement-evasion phenotypes, while comparative genomics suggests that several gene families and loci are potentially involved in host association. This multidisciplinary work provides novel insights into the functional evolution of host-adapted phenotypes, building a foundation for further investigation of the immunological and genomic determinants of host association. IMPORTANCE Host association is the phenotype that is commonly found in many pathogens that preferential survive in particular hosts. The Lyme disease (LD)-causing agent, B. burgdorferi (Bb), is an ideal model to study host association, as Bb is mainly maintained in nature through rodent and avian hosts. A widespread yet untested concept posits that host association in Bb strains is linked to Bb functional genetic variation conferring evasion to complement, an innate defense mechanism in vertebrate sera. Here, we tested this concept by grouping 20 Bb strains into three complement-dependent host-association phenotypes based on their survivability in sera and/or bloodstream and distal tissues in rodent and avian LD models. Phylogenomic analysis of these strains further correlated several gene families and loci, including ospC, with host-specific complement-evasion phenotypes. Such multifaceted studies thus pave the road to further identify the determinants of host association, providing mechanistic insights into host-pathogen interaction.