Molecular epidemiology of HIV among people who inject drugs after the HIV-outbreak in Athens, Greece: Evidence for a 'slow burn' outbreak

BACKGROUND

New diagnoses of HIV-1 infection among people who inject drugs (PWID) in Athens, Greece, saw a significant increase in 2011 and a subsequent decline after 2013. Despite this, ongoing HIV-1 transmission persisted from 2014 to 2020 within this population. Our objective was to estimate the time of infection for PWID in Athens following the HIV-1 outbreak, explore the patterns of HIV-1 dispersal over time, and determine the duration from infection to diagnosis.

METHODS

Time from HIV-1 infection to diagnosis was estimated for 844 individuals infected within 4 PWID-specific clusters and for 8 PWID infected with sub-subtype A6 diagnosed during 2010-2019. Phylogeny reconstruction was performed using the maximum-likelihood method. HIV-1 infection dates were based on molecular clock calculations.

RESULTS

In total 86 of 92 (93.5%) sequences from PWID diagnosed during 2016-2019 were either related to the previously identified PWID-specific clusters (n = 81) or belonged to a new A6 cluster (n = 5). The median time between infection and diagnosis was 0.42 years during the outbreak period and 0.70 years during 2016-2019 (p < 0.001). The proportion of clustered sequences from PWID was very low at 5.3% during the pre-outbreak period (1998-2009), saw an increase to 41.7% one year before the outbreak in 2010, and consistently remained high during the whole period after 2011, spanning the post-outbreak period (2016-2019) with a range from 92.9% to 100%.

CONCLUSIONS

The substantial proportion of clustered infections (93.5%) during 2016-2019 implies a persistent 'slow burn' HIV outbreak among PWID in Athens, suggesting that the outbreak was not successfully eliminated. The consistently high proportion of clustered sequences since the onset of the outbreak suggests the persistence of ongoing HIV-1 transmission attributed to injection practices. Our findings underscore the importance of targeted interventions among PWID, considering the ongoing transmission rate and prolonged time from infection to diagnosis.

The origin, dissemination, and molecular networks of HIV-1 CRF65_cpx strain in Hainan Island, China

BACKGROUND

HIV-1 CRF65_cpx strain carries drug-resistant mutations, which raises concerns about its potential for causing virologic failure. The CRF65_cpx ranks as the fourth most prevalent on Hainan Island, China. However, the origin and molecular epidemiology of CRF65_cpx strains in this area remain unclear. This study aims to estimate the spatial origins and dissemination patterns of HIV-1 CRF65_cpx in this specific region.

METHODS

Between 2018 and 2021, a total of 58 pol sequences of the CRF65_cpx were collected from HIV-positive patients on Hainan Island. The available CRF65_cpx pol sequences from public databases were compiled. The HIV-TRACE tool was used to construct transmission networks. The evolutionary history of the introduction and dissemination of HIV-1 CRF65_cpx on Hainan Island were analyzed using phylogenetic analysis and the Bayesian coalescent-based approach.

RESULTS

Among the 58 participants, 89.66% were men who have sex with men (MSM). The median age was 25 years, and 43.10% of the individuals had a college degree or above. The results indicated that 39 (67.24%) sequences were interconnected within a single transmission network. A consistent expansion was evident from 2019 to 2021, with an incremental annual addition of four sequences into the networks. Phylodynamic analyses showed that the CRF65_cpx on Hainan Island originated from Beijing (Bayes factor, BF = 17.4), with transmission among MSM on Hainan Island in 2013.2 (95%HPD: 2012.4, 2019.5), subsequently leading to an outbreak. Haikou was the local center of the CRF65_cpx epidemic. This strain propagated from Haikou to other locations, including Sanya (BF > 1000), Danzhou (BF = 299.3), Chengmai (BF = 27.0) and Tunchang (BF = 16.3). The analyses of the viral migration patterns between age subgroups and risk subgroups revealed that the viral migration directions were from "25-40 years old" to "17-24 years old" (BF = 14.6) and to "over 40 years old" (BF = 17.6), and from MSM to heterosexuals (BF > 1000) on Hainan Island.

CONCLUSION

Our analyses elucidate the transmission dynamics of CRF65_cpx strain on Hainan Island. Haikou is identified as the potential hotspot for CRF65_cpx transmission, with middle-aged MSM identified as the key population. These findings suggest that targeted interventions in hotspots and key populations may be more effective in controlling the HIV epidemic.

Advanced Genetic Methodologies in Tracking Evolution and Spread of SARS-CoV-2

A newly emerged coronavirus, SARS-CoV-2, caused severe pneumonia outbreaks in China in December 2019 and has since spread to various countries around the world. Here, we describe genetic methods to trace the evolution route and probe the transmission dynamics of this virus.

A comprehensive profile of genomic variations in the SARS-CoV-2 isolates from the state of Telangana, India

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 has rapidly turned into a pandemic, infecting millions and causing 1 157 509 (as of 27 October 2020) deaths across the globe. In addition to studying the mode of transmission and evasion of host immune system, analysing the viral mutational landscape constitutes an area under active research. The latter is expected to impart knowledge on the emergence of different clades, subclades, viral protein functions and protein-protein and protein-RNA interactions during replication/transcription cycle of virus and response to host immune checkpoints. In this study, we have attempted to bring forth the viral genomic variants defining the major clade(s) as identified from samples collected from the state of Telangana, India. We further report a comprehensive draft of all genomic variations (including unique mutations) present in SARS-CoV-2 strain in the state of Telangana. Our results reveal the presence of two mutually exclusive subgroups defined by specific variants within the dominant clade present in the population. This work attempts to bridge the critical gap regarding the genomic landscape and associate mutations in SARS-CoV-2 from a highly infected southern region of India, which was lacking to date.

Tuberculosis outbreak investigation using phylodynamic analysis

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Phylodynamic analysis gives insight into mycobacterium tuberculosis outbreaks.

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Robust estimation of epidemiological parameters in Bern thanks to high sampling rate.

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Infectious period for WTK cases significantly longer than in Bernese outbreak.

The fast evolution of pathogenic viruses has allowed for the development of phylodynamic approaches that extract information about the epidemiological characteristics of viral genomes. Thanks to advances in whole genome sequencing, they can be applied to slowly evolving bacterial pathogens like Mycobacterium tuberculosis. In this study, we investigate and compare the epidemiological dynamics underlying two M. tuberculosis outbreaks using phylodynamic methods. Specifically, we (i) test if the outbreak data sets contain enough genetic variation to estimate short-term evolutionary rates and (ii) reconstruct epidemiological parameters such as the effective reproduction number.

The first outbreak occurred in the Swiss city of Bern (1987–2012) and was caused by a drug-susceptible strain belonging to the phylogenetic M. tuberculosis Lineage 4. The second outbreak was caused by a multidrug-resistant (MDR) strain of Lineage 2, imported from the Wat Tham Krabok (WTK) refugee camp in Thailand into California.

There is little temporal signal in the Bern data set and moderate temporal signal in the WTK data set. Thanks to its high sampling proportion (90%) the Bern outbreak allows robust estimation of epidemiological parameters despite the poor temporal signal. Conversely, there is much uncertainty in the epidemiological estimates concerning the sparsely sampled (9%) WTK outbreak. Our results suggest that both outbreaks peaked around 1990, although they were only recognized as outbreaks in 1993 (Bern) and 2004 (WTK). Furthermore, individuals were infected for a significantly longer period (around 9 years) in the WTK outbreak than in the Bern outbreak (4–5 years).

Our work highlights both the limitations and opportunities of phylodynamic analysis of outbreaks involving slowly evolving pathogens: (i) estimation of the evolutionary rate is difficult on outbreak time scales and (ii) a high sampling proportion allows quantification of the age of the outbreak based on the sampling times, and thus allows for robust estimation of epidemiological parameters.

Characterization of Avian Influenza A (H7N9) Virus Prevalence in Humans and Poultry in Huai'an, China: Molecular Epidemiology, Phylogenetic, and Dynamics Analyses

OBJECTIVE

To trace the source of human H7N9 cases in Huai'an and elucidate the genetic characterization of Huai'an strains associated with both humans and birds in live poultry market.

METHODS

An enhanced surveillance was implemented when the first human H7N9 case was confirmed in Huai'an. Clinical specimens, cloacal swabs, and fecal samples were collected and screened by real-time reverse transcription-polymerase chain reaction (RT-PCR) for H7N9 virus. The positive samples were subjected to further RT-PCR and genome sequencing. The phylodynamic patterns of H7N9 virus within and separated from Huai'an and evolutionary dynamics of the virus were analyzed.

RESULTS

Six patients with H7N9 infection were previously exposed to live poultry market and presented symptoms such as fever (>38.0 °C) and headaches. Results of this study support the hypothesis that live poultry markets were the source of human H7N9 exposure. Phylogenetic analysis revealed that all novel H7N9 viruses, including Huai'an strains, could be classified into two distinct clades, A and B. Additionally, the diversified H7N9 virus circulated in live poultry markets in Huai'an. Interestingly, the common ancestors of the Huai'an H7N9 virus existed in January 2012. The mean nucleotide substitution rates for each gene segment of the H7N9 virus were (3.09-7.26)×10-3 substitutions/site per year (95% HPD: 1.72×10-3 to 1.16×10-2).

CONCLUSION

Overall, the source of exposure of human H7N9 cases in Huai'an was live poultry market, and our study highlights the presence of divergent genetic lineage of H7N9 virus in both humans and poultry specimens in Huai'an.

Phylogeny and population dynamics of respiratory syncytial virus (Rsv) A and B

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections in infants and young children. RSV is characterised by high variability, especially in the G glycoprotein, which may play a significant role in RSV pathogenicity by allowing immune evasion. To reconstruct the origin and phylodynamic history of RSV, we evaluated the genetic diversity and evolutionary dynamics of RSV A and RSV B isolated from children under 3 years old infected in Italy from 2006 to 2012. Phylogenetic analysis revealed that most of the RSV A sequences clustered with the NA1 genotype, and RSV B sequences were included in the Buenos Aires genotype. The mean evolutionary rates for RSV A and RSV B were estimated to be 2.1 × 10(-3) substitutions (subs)/site/year and 3.03 × 10(-3) subs/site/year, respectively. The time of most recent common ancestor for the tree root went back to the 1940s (95% highest posterior density-HPD: 1927-1951) for RSV A and the 1950s (95%HPD: 1951-1960) for RSV B. The RSV A Bayesian skyline plot (BSP) showed a decrease in transmission events ending in about 2005, when a sharp growth restored the original viral population size. RSV B BSP showed a similar trend. Site-specific selection analysis identified 10 codons under positive selection in RSV A sequences and only one site in RSV B sequences. Although RSV remains difficult to control due to its antigenic diversity, it is important to monitor changes in its coding sequences, to permit the identification of future epidemic strains and to implement vaccine and therapy strategies.