A changing hepatitis B virus genetic diversity pattern in North-western Tanzania: Is it a concern for Tanzania?

doi:10.21203/rs.3.rs-5123901/v1

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A changing hepatitis B virus genetic diversity pattern in North-western Tanzania: Is it a concern for Tanzania?

https://doi.org/10.21203/rs.3.rs-5123901/v1

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Background

Frequent evaluation and understanding of the genetic diversity of the HBV virus in different affected global settings is essential towards the elimination of infection by 2030. In this regard, HBV genetic diversity evaluation is scarcely done in Tanzania, imposing a crucial knowledge gap. We serologically and genetically characterized the HBV from 21 chronically HBV-infected patients attending Bugando Medical Centre to determine the HBV genetic diversity.

Methods

This cross-sectional study was conducted on the selected 21 plasma samples with high HBV-deoxyribonucleic acid (DNA) levels of > 300,000IU/mL. DNA extraction was done using Qiagen DNA Blood Mini Kit (Qiagen, Hilden, Germany). The Partial amplification of HBV DNA, sequencing and analysis was done at Institute of Virology, Giessen Germany.

Results

The mean age of 21 HBV chronically infected patients was 41 ± 11 years with HBV-DNA median of 979 [185.5–8457.5] IU/mL. Majority (85.7%, 18/21) were males from Mwanza. The genotypes detected were HBV/A; 76.2% (16/21), all being A1, followed by HBV/D; 19% (4/21), all being D4 and lastly HBV/G, 4.8% (1/21). The HBV/A1 serotypes were Adw2; 81.3% (13/16), followed by Ayw2; 12.5% (2/16) and all 4 HBV/D4 genotypes were serotype Ayw2. Overall, 19% (4/21) of the patients had HBV escape mutations (T123V, Y134N, P120T and T123A). The HBV/A identified in this study were distributed randomly among other HBV/As from all regions of Tanzania reported previous. On the other hand, HBV/D identified in this study were distributed among HBV/Ds from the North-western Tanzania identified previously. However, most of the HBV/As and all of the HBV/Ds identified in this study did not mix-up with HBV/As and HBV/Ds from other parts of the world.

Conclusion

HBV/A (HBV/A1) is predominant over time in North-western Tanzania. Most HBV/A1 and all HBV/D are unique to Tanzania as had been previously reported. However, the molecular epidemiology of HBV in this region is changing with occurrence of HBV/G as a new genotype and increasing HBV escape mutations which are mostly not due to drug pressure selection. The observation of HBV escape mutations threatening the future efficacy of serologic diagnostic tests and HBV vaccination in Tanzania underscoring the continuous monitoring of these mutants.

Biological sciences/Microbiology/Virology

Biological sciences/Microbiology/Virology/Hepatitis b virus

Chronic HBV infection

HBV genotypes

HBV-escape mutations

North-Western Tanzania

Hepatitis B virus is a prototype of hepatotropic circular and partially double-stranded DNA viruses known as the Hepadnaviridae family [1, 2]. Human HBV belongs to Orthohepadnavirus and has many genotypes among the mammals involved [2]. The genome of HBV ranges from 3,182 bp (Genotype D)[3, 4] to 3,248 bp (Genotype G) [5]. The HBV genome is organized into eleven genes, four highly overlapping structural genes or open reading frames (ORFs) which are polymerase (pol) ORF, PreCore/Core (PreC/C) ORF, Pre surface/surface (PreS/S) ORF, and Protein X (X)-ORF, and seven being regulatory sequences which are direct repeat 1 and 2 (DR1 and DR2 respectively), and enhancer region 1 and 2 (EN-I and EN-II respectively), Promoter I, Promoter II, and basic core protein (BCP) [5, 6]. As a para-retrovirus, HBV replicates through a pregenomic RNA intermediate (pgRNA) generated from transcription of covalently closed circular DNA (cccDNA) by host cell enzymatic machinery in the nuclear of the hepatocyte [7]. The reverse transcription is carried out by a viral encoded reverse transcriptase (RT), which lacks a 5’-3’ exonuclease for proofreading and is hence prone to mutations at the rate of 1.4–3.2 × 10^− 5 base substitutions/site/year [8]. Other mechanisms involved are human migration and viral recombination in cases of HBV genotype or subgenotype coinfection [9]. HBV mutation can occur in any genomic region, producing variants having different clinical implications and severity [10].

Currently, there are 10 known HBV genotypes (HBV/A-J), about 44 sub-genotypes, 9 serotypes, as well as several variants involving all four ORFs of HBV [11]. HBV genotypes/sub-genotypes and serotypes have all been shown to influence the transmission, pathogenesis, variant occurrences, and geographical distribution. In turn, variants influence the treatment, vaccine response, and HBV diagnostic failure [12]. Globally, the contribution of HBV genotypes is as follows: HBV/C (26.1%), HBV/D (22.1%), HBV/E (17.6%), HBV/A (16.9%), HBV/B (13.5%), and the other genotypes (HBV/F/G/H/I/J and recombinants) are < 2% each. There are differences in predominant HBV genotypes in different regions: America (America-HBV/H > HBV/G,) Asia (HBV/C > HBV/D > HBV/B > HBV/A > HBV/Recombinants) Europe (HBV/D), Northern Africa (HBV/D > HBV/E), Middle Africa (HBV/A > HBV/E), Western Africa (HBV/E > > HBV/A), Southern Africa (HBV/A), and Eastern Africa (HBV/A > > HBV/D > > HBV/E) [13]. In Tanzania, genotypes reported from previous studies conducted among blood donors include A (86.9%), A1 (100%), and D (29%). Genotype HBV/E has also been reported [14]. These genotypes are distributed as follows: Northern Zone: HBV/A (all being HBV/A1) and HBV/D, Eastern Zone; HBV/A (all being HBV/A1) and HBV/D, Southern Zone; HBV/A (all being HBV/A1), Western Zone; HBV/A (all being HBV/A1) and HBV/D, Zanzibar; HBV/A (all being HBV/A1), North-western Tanzania (Lake Zone); HBV/A (all being HBV/A1), HBV/D, and HBV/E, Southern High-lands; HBV/A (all being HBV/A1), HBV/D, and HBV/E, and Zanzibar; HBV/A (all being HBV/A1) [14]. With respect to HBV infection prevention and treatment, HBV surface and polymerase genes are important for frequent molecular evaluation. Both natural infection and vaccination target the HBsAg in the second hydrophilic loop (139 to 147 or 149 aa) by producing hepatitis B surface antibodies (anti-HBs). This provides protection against all HBV genotypes and sub-genotypes and is responsible for the broad immunity afforded by HBV vaccination. However, mutations within this region of the HBV surface antigen have been reported [15].

HBV escape mutations can be grouped into two groups: mutations associated with diagnostic failure and mutations associated with immune escape. Reported mutations that are associated with diagnostic failure include P120T, T126S, Q129H, G130N, S143L, D144A, and G145A/R, and those associated with immune escape include mutations at positions 120, 126, 129, 130, 133, 134, 137, 140, 143, 144, and 145 [12]. Prevalences of these mutations have been shown to increase over time [16, 17] and patient’s age [18]. Therefore, these HBV escape mutations can occur in a previously mutation-free WHO-HBV epidemiological region, and hence, frequent HBV escape mutation analysis in the respective region is necessary. On the other hand, several mutations involving the polymerase gene with reduced efficacy of anti-HBV antiviral drugs such as tenofovir (TDF) and entecavir (ETV) have been reported [10]. Polymerase mutations can be analyzed by either targeted partial or whole genome sequence analysis. In Tanzania, molecular characterization of HBV has been scarcely done on the HB-S gene in blood donors, reporting HBV/A, D, and E as well as negligible (0.4%) escape mutations in HBV/A and 0% of antiviral drug resistance-associated mutations. The HBV escape mutations reported are A128V, Q129H, and M133T in HBV/A and none in both HBV/D and HBV/E[14]. Contrary to blood donors, who are likely to be young and at their early stage of HBV infection, chronically HBV-infected patients are more likely to be older and at more advanced stages of the infection. Both age and duration of infection are known to influence the pattern of HBV molecular characteristics by selection and occurrence of mutations. With the exception of this study, an HBV molecular characterization study had not previously been performed among the chronically HBV-infected patients in Tanzania, who are more likely to be older and have a longer duration of infection than the blood donors, thus creating a knowledge gap of this crucial information required in the race of eliminating HBV infection by 2030. This study therefore addressed this concern by partial sequencing of the HBV surface and polymerase genes among chronically HBV-infected patients attending Bugando Medical Centre, a tertiary referral hospital in northern-western Tanzania.

Ethical approval and consent to participate

The samples were from another study conducted from May 2023 to October 2023 which was approved by the joint Catholic University of Health and Allied Sciences/Bugando Medical Centre (CUHAS/BMC) research ethics and review committee (CREC/663/2023). "The need for informed consent was waived by CUHAS/BMC research and review committee.". Permission to use archived plasma specimens and to conduct the study at Bugando Medical Centre was from the previous study which was granted by the Bugando Medical Centre management (AB.286/317/01/PART "M"). All retrospective data were accessed with fully anonymity by using their hospital registration number from the Bugando Medical Records. After retrieving, the participants were given study identification number. These study identification numbers were used in all data analysis and communication related to the study. All data were treated with maximum confidentiality. All laboratory processes and experiments were performed in accordance with relevant guidelines and regulations.

Study design, duration, area, population and sample size

This retrospective laboratory-based cross-sectional study had 21 purposively sampled from archived plasma specimens of chronically Hepatitis B virus (HBV)-infected patients attending at Bugando Medical Centre in Mwanza, Northern-Western Tanzania.

Inclusion and exclusion criteria

The study included plasma samples from repeatedly confirmed HBsAg-positive patients for more than six months. Included were all plasma samples of patients with HBV-deoxyribonucleic acid (DNA) levels > 300,000 IU/mL and an available volume of > 300µL. All plasma remnants with volume < 300µL were excluded.

Data and plasma samples sorting

Demographic data and clinical data, including HBV-DNA, alanine amino transferase (ALT), aspartate amino transferase (AST), and full blood picture (FBP) parameters were collected by using a checklist from a medical record database. Plasma samples with > 300 uL and HBV-DNA level results of > 300,000 IU/mL were sorted and stored at -80°C in the Bugando Medical Centre (BMC) Molecular laboratory until further analysis.

DNA extraction, amplification, and sequence analysis

A total of 200 µl of thawed plasma samples were drawn from each sample and used for DNA extraction using the Qiagen DNA Blood Mini Kit (Qiagen, Hilden, Germany) following manufacturer instructions [19]. The extracted DNA in Eppendorf tubes was packed in tight double plastic bags and transported to Germany for amplification, sequencing, and sequence analysis as previously described [20]. Genotyping using the HIV Stanford database [21] and GenoPheno2hbv 2.0 [22], NCBI HBV genotyping tool [23] and hepatitis B database (HBVdb) tool [24] was performed to determine HBV genotypes, subgenotypes and mutation pattern.

Phylogenetic analysis

Phylogenetic analysis was performed using the A la Carte Mode, which is a package of Methodes et Algorthmes pour la Bio-Informatique (MABL)-Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université Montpellier, North-West of Montpellier, France. The procedure involved four steps. The first step was multiple alignment using MUSCLE, the second step was alignment curation using Gblocks, the third step was construction of the phylogenetic tree using the Maximum Likehood (PhylML), and the fourth and last step was visualization of the tree using TreeDyn [25]. The bootstrap was set at 100.

Comparative phylogenetic Analysis

A combined comparative phylogenetic analysis was performed. The local comparative phylogenetic analysis involved the current study HBV surface/partial polymerase sequences and previously obtained sequences from other previous studies done in Tanzania that were found in the NCBI nucleotide database [26]. The global comparative phylogenetic analysis involved sequences from the current study and those from other parts of the world, which were selected automatically by the HIV/HBV Stanford database [21]. The procedure involved preparation and uploading of the local comparative phylogenetic library into the HIV/HBV Stanford database, followed by construction of the comparative phylogenetic tree by using the Interactive Tree of Life (iTOL) [27, 28].

Preparation of the local comparative phylogenetic library

Local HBV/A comparative phylogenetic library

The library created contained 102 HBV/A sequences, of which 16 were from the current study and 86 sequences were from the previous study. HBV/A surface sequences from previous studies done in Tanzania were searched and downloaded from the NCBI nucleotide database. HBV/A surface sequences from previous studies found in the NCBI were 672, which were distributed as follows: North-western (Lake Zone) (TZLK) 304; Eastern Zone (TZE) 186; Southern Zone (TZS) 94; Southern Highlands Zone (TZSH) 32; Zanzibar (TZZN) 29; Northern Zone (TZN); 20; Western Zone (TZW) 6; and Unguja (TZUN) 1 [26]. The 86 sequences were obtained by using systematic cluster sampling, in which 30 sequences from the TZLK were obtained by sampling every 10th sequence, 10 sequences from the TZE were obtained by sampling every 18th sequence, 10 sequences from the TZS were obtained by sampling every 9th sequence, 10 sequences from the TZSH were obtained by sampling 3rd sequences, 9 sequences from the TZZN by sampling every 3rd sequence, 10 sequences from the TZN by sampling every 2nd sequences, all of the 6 sequences from the TZW, and 1 sequence from the TZUN.

Local HBV/D comparative phylogenetic library

The library created contained 99 HBV/D sequences in which 4 sequences were from the current study and 95 sequences were from the previous study. HBV/D surface sequences from previous study done in Tanzania were searched and downloaded from the NCBI nucleotide database. HBV/D surface sequences from previous study found in the NCBI were 95 and distributed as follows:- North-western (Lake Zone) (TZLK) 68; Eastern Zone (TZE) 22; Southern highlands Zone (TZSH) 2; Northern Zone (TZN) 2; and Western Zone (TZW) 1[26]. All of the sequences from all of Zones were sampled.

Comparative phylogenetic tree construction and annotation

The library created contained 99 HBV/D sequences, of which 4 sequences were from the current study and 95 sequences were from the previous study. HBV/D surface sequences from previous studies done in Tanzania were searched and downloaded from the NCBI nucleotide database. HBV/D surface sequences from previous studies found in the NCBI were 95 and distributed as follows: North-western (Lake Zone) (TZLK) 68; East Zone (TZE) 22; Southern Highlands Zone (TZSH) 2; North Zone (TZN) 2; and West Zone (TZW) 1 [26]. All of the sequences from all of the zones were sampled.

Data management and analysis

Demographic, HBV-DNA levels, ALT, AST, and platelet parameters were extracted from medical records and then, along with serotype, genotype and mutation data, were entered and cleaned using Microsoft Excel 2016. APRI scores were calculated according to the respective formula [29]. HBV-DNA result values of target not detected (TND), < 20 IU/mL, and > 1.7 X10⁸ were treated as 0, 20, and 1.7 X10⁸ IU/mL, respectively. STATA software version 15 was used to analyze the data. Continuously skewed data were summarized using a medium and an interquartile range (IQR), while normally distributed data were summarized using the mean and standard deviation. Categorical data such as sex, genotypes, and mutations were summarized using proportion (percent). We used two sample proportion tests to compare the significance of proportional differences of HBV escape mutation between current and previous studies. The p-value significance was set at < 0.05 and the confidence interval (CI) at 95%. Sequences datasets generated and analysed during obtained in the current study were also submitted to GenBank and therefore available in this system with accession number from PQ446445-PQ446465.

Patients’ social demographic and clinical data

Of the 22 purposively selected DNA samples with high HBV-DNA levels > 300,000 IU/mL, 21 were amplified and therefore sequenced. One sample (HBV_TZ 19) could not be amplified, possibly due to a mutation at the primer binding site. HBV chronically infected patients (21) had a mean age of 41 ± 11 years. Most of them, 85.7% (18/21) were male, and many, 38.1% (8/21) were from the Mwanza region. The median HBV-DNA levels were 979 [185.5–8457.5] IU/mL. Nevertheless, these patients had ALT levels with a median of 90.3 [55.9-185.7], with the majority, 81% (17/21) having levels above 41 U/L. They also had AST levels with a median of 168.0 [55.2–309.5], and most of them, 81% (17/21) had levels above 40 U/L. The APRI score was 2.7 [0.9–3.3] with more than half, 66.7% (14/21), of the patients having levels of more than 1 score (Table 1).

Table 1

Demographic and clinical data
Demographic characteristics	ALL (21) n (%)
Age (Years)
Mean (SD)	41 (± 11)
Age ≤ 20 years old, n (%)	1 (4.8)
Age > 20 years old, n (%)	20 (95.2)
Age ≤ 30 years old, n (%)	4 (19.0)
Age > 30years old, n (%)	17 (81.0)
Sex, n (%)
Female	3 (14.3)
Male	18(85.7)
Residence (Region), n (%)
Mwanza	8 (38.1)
Geita	5(23.8)
Tabora	3(14.2)
Shinyanga	2 (9.5)
Arusha	1 (4.8)
Katavi	1(4.8)
Mara	1(4.8)
Clinical characteristics
HBV-DNA levels (IU/mL)
Median [IQR]	979 [185.5–8457.5]
ALT (U/L)
Median [IQR]	90.3 [55.9-185.7]
Less than 41, n (%)	4 (19.0)
More than 41, n (%)	17 (81.0)
AST (U/L)
Median [IQR]	168.0 [55.2-309.5]
Less than 40, n (%)	4 (19.0)
More than 40, n (%)	17 (81.0)
APRI score
Median [IQR]	2.7 [0.9–3.3]
Less than 0.5, n (%)	5 (23.8)
More than 0.5 but less than 1, n (%)	2 (9.5)
More than 1, n (%)	14 (66.7)
HBVL: Hepatitis B viral load, SD: Standard deviation, IQR: Interquartile range

General molecular characteristics

The predominant genotype was HBV/A, 76.2% (16/21), followed by HBV/D, 19% (4/21) and the last was HBV/G, 4.8% (1/21). All HBV/A were sub-genotype A1, and all HBV/D were sub-genotype D4. Serotypes in HBV/A1 were Adw2, 81.3% (13/16), followed by Ayw2, 12.4% (2/16), and the least was Adw1, 6.3% (1/16) (Table 2), while all HBV/D4 genotypes were Ayw2.

Table 2

HBV-genotypes, sub-genotypes and serotypes
HBV genotype, n (%)	Sub-genotypes, n (%)	Serotypes, n (%)
A, 16 (76.2)	A1, 16 (100)	Adw1, 1 (6.3)
		Adw2, 13(81.3)
		Ayw2 2, (12.4)
D, 4 (19)	D4, 4 (100)	Ayw2, 4 (100)
G, 1 (4.8)	-	Ayw1

Hepatitis B escape mutations and the characteristics of the patients with versus without hepatitis B escape mutations

Out of 21 sequenced samples, 4 (19%) had HBV escape mutations. The escape mutations identified were T123V, Y134N, P120T, and T123A. These four patients with HBs-escape mutations had a median age of 48 [44-52.5] years, and all were male. None of the 21 patients studied had antiretroviral drug resistance associated mutation. Of these patients with HBV escape mutations, 2/4 (50.0%) were from Shinyanga, and the rest, 2/4 (50%), were from Geita and Mwanza, one patient from each region. All four patients had HBV DNA levels ranging from 553,996 IU/mL to 2,000,000 IU/mL. Among these four patients, two had an HBV/A genotype, and the other two had an HBV/D genotype. On the other hand, patients without HBV escape mutations were 81% (17/21). These patients had a median age [IQR] of 31 [31–47] years, and the majority of them, 77.8% (14/17), were male (Table 3). The overall proportion of patients with HBV escape mutation was significant lower compared to those without escape mutation (19% versus 81%, p-value < 0.005%) in current study (Table 4). However, escape mutation showed to increase significantly among HBV/A (0.4% versus 12.5%, p-value < 0.005%) and HBV/D (0% versus 50%, p-value < 0.005%) compared to previous findings in 2017 (Table 5).

Table 3

Characteristics of patients with versus without HBV escape mutations
HBV-TZ no:	Region	HBV genotype	HBV (IU/mL)	ALT (U/L)	AST (U/L)	APRI (scores)	Escape mutation	On ARV	Type of ARV
Patients with escape mutations
HBV_TZ 04	Mwanza	D	914000	56.91	100.93	4.3	T123V, Y134N	NO
HBV_TZ 12	Geita	A	669316	90.29	320.25	2.6	P120T	NO
HBV_TZ 13	Shinyanga	A	2000000	69.10	221.46	3.0	P120T	NO
HBV_TZ 15	Shinyanga	D	553996	44.63	65.49	1.5	T123A	YES	TDF
Patients without escape mutations
HBV_TZ 01	Geita	A	> 1.7X10⁸	156.50	153.56	3.3	NO	NO	-
HBV_TZ 02	Mwanza	A	383000	19.40	20.00	0.2	NO	NO	-
HBV_TZ 03	Geita	A	474349	700.00	700.00	7.2	NO	NO	-
HBV_TZ 05	Tabora	A	3070011	56.97	233.90	1.2	NO	NO	-
HBV_TZ 06	Mwanza	G	548079	225.00	138.64	4.2	NO	NO	-
HBV_TZ 07	Mwanza	A	> 1,785,715	56.91	100.90	4.3	NO	NO	-
HBV_TZ 08	Geita	D	8028905	580.84	381.87	4.3	NO	NO	-
HBV_TZ 09	Katavi	A	485156	23.50	31.50	0.4	NO	YES	TDF
HBV_TZ 10	Mwanza	A	7952789	90.37	55.16	0.5	NO	NO	-
HBV_TZ 11	Mwanza	A	5425918	55.86	41.29	0.9	NO	NO	-
HBV_TZ 14	Mwanza	A	> 1,785,715	98.85	280.80	3.2	NO	NO	-
HBV_TZ 16	Tabora	D	1030145	185.68	667.94	2.7	NO	YES	TDF
HBV_TZ 17	Mwanza	A	1610055	200.86	340.65	3.3	NO	NO	-
HBV_TZ 18	Mara	A	> 1,785,715	85.32	168.02	4.3	NO	NO	-
HBV_TZ 19	Mwanza	A	688085	120.40	270.70	1.3	NO	NO	NO
HBV_TZ 20	Arusha	A	600499	28.71	27.36	0.4	NO	NO	NO
HBV_TZ 21	Tabora	A	> 1,785,715	258.94	309.52	2.7	NO	NO	NO

Table 4

Proportion of HBV escape mutation in the current study
Characteristic	No HBV escape mutation		Prescence of HBV escape mutation		p-value
Characteristic	Proportion (%)	95% CI	Proportion (%)	95% CI	p-value
Overall	81	64.2–97.8	19	2.2–35.8	< 0.005
HBV/A	87.5	71.3–100	12.5	3.7–28.7	< 0.005
HBV/D	50	10–99	50	10–99	1.00

Table 5

Change in proportion of HBV escape mutation between 2017 and the current study
Characteristic	HBV escape mutation in 2017		HBV escape mutation in the current study		p-value
Characteristic	Proportion (%)	95% CI	Proportion (%)	95% CI	p-value
Overall	0.4	0.04–0.9	19	2.2–35.8	< 0.005
HBV/A	0.4	0.08–0.9	12.5	3.7–28.7	< 0.005
HBV/D	0.0		50	1–99	< 0.005

Phylogenetic analysis

All 21 HBV sequenced are closely related according to their respective genotypes (Fig. 1).

Combined local and global comparative phylogenetic analysis for HBV/A

Combined local and global phylogenetic analysis showed that all of the HBV/A isolates obtained in this current study clustered randomly with previous isolates obtained from other regions of Tanzania. However, as it is for other previous isolates, most of the isolates of this current study did not mix-up with other isolates from outside Tanzania (Fig. 2).

Combined local and global comparative phylogenetic analysis for HBV/D and HBV/G

Combined local and global phylogenetic analysis showed that all of the HBV/D isolate obtained in this current study clustered with previous isolates obtained from Tanzania Northern and Lake Zones. Both of the current and the previous HBV/D isolates from Tanzania did not mix-up with other isolates from outside Tanzania (Fig. 3).

The phylogenetic tree was created by Methodes et Algorthmes pour la Bio-Informatique (MABL)-Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM), Université Montpellier, North-West of Montpellier, France. The branch length is proportional to the number of substitutions per site[25].

Coloured and non-coloured isolates are HBV/A from within and outside Tanzania respectively. Sequences obtained from this current study are coloured blue. All non-blue coloured sequences are from previous study performed in Tanzania. The initials indicate different parts of Tanzania. TZLK: Tanzania Lake Zone, TZE: Tanzania Eastern Zone, TZSH: Tanzania Southern Highlands Zone, TZS: Tanzania Southern Zone, TZN: Tanzania Northern Zone, TZW: Tanzania Western Zone, TZZN: Tanzania Zanzibar, and TZU: Tanzania Unguja. The local comparative phylogenetic was created using HIV/HBV Stanford database[21] and the Interactive Tree of Life (iTOL)[27, 28].

Coloured and non-coloured isolates are HBV/D and/or HBV/G from within and outside Tanzania respectively. Sequences obtained from this current study are coloured blue. All non-blue coloured sequences are from previous study performed in Tanzania. The initials indicate different parts of Tanzania. TZLK: Tanzania Lake Zone, TZE: Tanzania Eastern Zone, TZSH: Tanzania Southern Highlands Zone, TZS: Tanzania Southern Zone, TZN: Tanzania Northern Zone, TZW: Tanzania Western Zone, TZZN: Tanzania Zanzibar, and TZU: Tanzania Unguja. The local comparative phylogenetic was created using HIV/HBV Stanford database[21] and the Interactive Tree of Life (iTOL)[27, 28].

In this study, we have determined the changing of HBV genetic diversity in Tanzania with the occurrence of new hepatitis genotypes. Among the 21 chronic hepatitis B-infected patients attending the Bugando Medical Centre, 16 (76.2%) had HBV/A (all being HBV/A1), 4 (19%) had HBV/D (all being HBV/D4), and 1 (4.8%) had HBV/G. The identification and report of HBV/G is believed to be the first report in Tanzania, to the best of our knowledge. Additionally, 19% (4/21) of the patients had HBV escape mutations, which were distributed as follows: one patient had T123V and Y134N; two patients had P120T; and one patient had T123A. Although antiretroviral drug resistance-associated mutations were not observed, a significant increase in the proportion of HBV escape mutations among HBV/A and HBV/D with reference to previous study was observed, threatening the future efficacy of serological diagnostic techniques and the HBV vaccine in the country.

In this current study, three types of HBV genotypes were identified (HBV/A, HBV/D, and HBV/G), with the predominance of HBV/A and HBV/A1 as previously reported in Tanzania [14]. This observation shows that, HBV/A and HBV/A1 are predominant in Tanzania over time since 2017. This observation shows that HBV/A and HBV/A1 are predominant in Tanzania over time since 2017. Similarly, predominance of HBV/A1 has been reported elsewhere [29, 30]. Moreover, the predominance of HBV/A1 in this study supports the assumption that Tanzania is a part of the geographic origin of HBV/A1, as it has been previously supported [14].

Although not significantly (p-value of 0.6921), the proportion of HBV/D observed in the current study was higher (19% = 4/21) than what had been reported (12.3% = 95/772) by a previous study in Tanzania [14]. The difference could be attributed to differences in sample sizes and study populations. The effect of the sample size is similar to what has been explained in HBV/A above. Contrary to the previous study, which used blood donors, this study used the chronic hepatitis B population. HBV/D is likely to dominate in the chronic infection state since it has a high tendency for chronicity development compared to HBV/A, which dominates more in the acute and early stages of the infection [31]. In this index study, we also observed a predominance of serotype adw2 by 66.7% (14/21). The predominance of serotype Adw2 has been reported in Uganda [32], Ethiopia[33], and globally [34].

We also identified HBV/G in our study for the first time. This patient (TZ_HBV 06) was genotyped HBV/A by using the HIV Stanford database [21] and GenoPheno2hbv 2.0 [22]. However, TZ-HBV 06 was genotyped HBV/G based on the NCBI HBV genotyping tool [23] and hepatitis B database (HBVdb) tool [24]. Contrary to the HIV/HBV Stanford database and GenoPheno2hbv, NCBI genotyping and HBVdb tools use single parallel rather than serial multiple alignment input. For example, the NCBI genotyping tool uses cumulative scores of BLAST pairwise alignments between overlapping segments of a query sequence and a reference sequence for each virus for resolving the inconclusive hepatitis B genotype [35]. Genotyping methods relying upon multiple alignments of a query sequence and the reference sequences suffer the impossibility of an automatic viral sequence alignment due to viral genome variability [35]. These non-automatic multiple alignment methods can draw the wrong HBV genotype. This patient with HBV/G had high HBV-DNA levels of about 5.5 x 105 IU/mL, ALT levels of 225 uL, and an APRI score of about 4.3. The high HBV-DNA levels and remarkable markers of inflammatory liver diseases observed in this patient with HBV/G could be attributed to impaired anti-viral interferon mechanisms due to the inability of HBeAg secretion due to the to the presence of a double stop codon in the HBV/G. This phenomenon not only allows the establishment of persistent HBV infection but also creates a conducive environment for unchecked high viral replication, resulting in chronically elevated liver inflammation [36, 37]. Another contribution to high levels of HBV-DNA and elevated liver inflammatory markers could be due to the to the increased replication rate of the virus. This phenomenon is attributed to a 36-nucleotide insertion that leads to upregulation of core protein expression [38, 39] which is essential for HBV/G replication [40]. HBV/G is being reported for the first time in Africa, particularly in northern-western Tanzania. Since the description of HBV/G in San Francisco, California, in the United States of America (USA) [41] and in France [42] to its’ full recognition as a separate hepatitis B genotype in Atlanta, Georgia, USA, and in Lyon, France [43], this genotype has never been described elsewhere in Africa before this current study.

Observation of HBV/G in Tanzania can be due to either of the two possibilities. First, although the geographic origin of HBV/G has been unclear since its discovery [44], the possible Africa geographic origin has been proposed [45] due to its similarity with HBV/E, which is endemic in Africa, particularly West Africa [46]. HBV/E has also been reported in other African countries, including the Congo, Democratic Republic of the Congo, Madagascar, Sudan, Uganda, Kenya [30] and Tanzania [14, 30]. Another possible explanation for the occurrence of HBV/G in Tanzania could be due to inter-continental interaction through human migration searching for new opportunities, such as mining activities. The patient with HBV/G in this study was diagnosed a few years after starting to work with North-Mara Barrick Mining in the Mara region. The diagnosis followed after the patient attended a nearby health facility complaining of generalized malaise, loss of appetite, and yellowish coloration of the eyes. The North-Mara Barrick Mining Company has workers originating from different parts of the world, including the America and Europe continents. This creates an inter-population social interaction with the potential for sexual behavior interaction, resulting in the transmission of the American genotype (HBV/G) from America and Europe into Tanzania. If this circumstance is true, then the HBV/G will be regarded as a migration HBV genotype.

On comparative phylogenetic analysis, all of the HBV/A isolates obtained in this study clustered randomly with previous isolates obtained from other regions of Tanzania, showing high diversity. However, as it is for other previous isolates, most of the isolates of this study did not mix up with other isolates from outside Tanzania. These findings support Tanzania to be part of the geographic origin of HBV/A1 [14], which further fortifies the hypothesis of the East African origin of HBV/A1 [29, 47, 48]. On the other hand, all of the HBV/D isolates obtained in this study clustered with previous isolates obtained from the Northern and Lake Zones of Tanzania and did not mix up with HBV/D isolates from outside the country. The fact that the HBV/D strains observed in this study did not mix up with other HBV/D strains from other East African countries, including Kenya [49, 50], Uganda [32], Rwanda [30] and Sudan [51] suggests that the observed HBV/D subtype in this study might be new and originating solely from Tanzania. This observation was also reported by the previous study in Tanzania and suggested that the previous identified genotype could be the new HBV/D clade originating in Tanzania [14]. The HBV/G isolate obtained from this study clustered with HBV/A isolates in both comparative and non-comparative phylogenetic analyses. This could be due to the fact that the NCBI HBV genotyping tool [23] and hepatitis B database (HBVdb) tool [24] that were able to pick and differentiate the HBV/G from HBV/A could not perform phylogenetic analysis and therefore were not used for phylogenetic analysis. On the other hand, the phylogenetic analysis tools used were the Methodes et Algorthmes pour la Bio-Informatique LIRMM (MABL-LIRMM) [25], and HIV/HBV Stanford database [21], which uses serial rather than parallel multiple alignment approaches. The Interactive Tree of Life (iTOL) tool [27, 28], which was used for annotation, received the already constructed phylogenetic tree in a format of Nexus text tree format created by using the HIV/HBV Stanford database [21].

In this index study, we found an HBV escape mutation of 12.5% (2/16) in HBV/A, 50% (2/4) in HBV/D, and 0% (0/1) in HBV/G, for an overall of 19% (4/21) in the whole study. Although the overall HBV escape mutation proportion increase in this study was non-significantly higher, a significant high proportion increase of escape mutation was observed in HBV/A (p-value < 0.005) and HBV/D (p-value < 0.005) compared to what had been reported previously in Tanzania in 2017 [14]. The difference could be due to the fact that the previous study population consisted of blood donors who were likely to be young and in their early stages of HBV infection, whereas the current study population is composed of chronic HBV-infected patients who are likely to have a long-standing duration of infection. The differences in study population can be further supported by several studies that have shown that HBV escape mutations can increase over time [16, 17] and with patients’ ages [18]. The proportion of HBV escape mutation (12.5%) in HBV/A was slightly lower than that of 14.9% (38/255) reported in the previous study conducted elsewhere in Europe [52]. Contrary to the previous study in Europe, which was composed of anti-HBV drug-experienced patients, all of the patients with HBV/A in the current study were not on anti-HBV drugs. Anti-HBV antiretroviral drugs have been shown to select and increase the occurrence of HBV escape mutations among patients receiving antiretroviral therapy [53]. The same previous study in Europe reported 25.3% (145/573) in HBV/D [52], which was lower than that of 50% (2/4) reported by our current study. The difference could be attributed to differences in sample size. The sample size in the previous study in Europe for HBV/D was 573, while in the current study for HBV/D it was 4. However, both the previous study in Europe and the current study in Tanzania showed HBV/D to have a higher proportion (25.3% and 50%) of HBV escape mutations than HBV/A (14.8% and 12.5%) respectively. Although the current study has identified and reported new escape mutations (P120T, T123A, and Y134N) in Tanzania, these mutations have been identified by the previous study in Europe, which involved chronically infected patients similar to the current study [52], contrary to the previous study in blood donors in Tanzania in 2017 [14]. However, contrary to the previous study in Europe, which involved chronically HBV-infected patients on antiretroviral therapy [52], most patients (75% = ¾) in the current study were not on antiretroviral treatment. This observation could be indicating that the HBV escape mutation observed in this current study is mostly not due to antiretroviral drug pressure selection. The possible explanations for the occurrence of these HBV escape mutations in this current study could be due to natural selection related to the inherent viral factors, immune selection pressure related to the infected patients, or environmental factors related to direct acquisition of an escape variant during the course of viral transmission. Based on inherent viral factors, HBV/D is believed to have a higher frequency of developing mutations, which are the precore A1896 mutation and the basal core promoter A1762T/G1764A mutation, than HBV/A [31]. This virological implication difference between HBV/D and HBV/A is not well documented in other types of mutations, such as escape mutations. Moreover, this concept cannot be implicated in our findings, as each of the HBV/A and HBV/D contributed equally among those patients with HBV escape mutations. Although the immunological selection pressure analysis needed more investigations, which were out of scope of this current study, the liver inflammatory markers signified by ALT were not significantly elevated and only taken at once, making immunological assessment difficult. Therefore, the environment factor related to direct acquisition of the escape variants stands in the lead to explain the possible source of the variants in this current study.

Our findings show that HBV/A (HBV/A1) is predominant over time in Tanzania. Most HBV/A1 and all HBV/D are unique to Tanzania, which possibly suggests that, as part of East Africa, Tanzania is part of the origin of HBV/A1 and the origin of the new HBV/D clade. The molecular epidemiology of HBV is changing with the occurrence HBV/G as a new genotype in the region and with a significant high proportion of HBV escape mutations, which are mostly not due to drug pressure selection. The possible increase of HBV escape mutations threatens the efficacy of diagnostic serological tests and HBV vaccination in the region. In addition to calling upon a bigger and more multicentred study so as to solidify the findings of this current study and evaluate the source of HBV escape mutations, we recommend HBV molecular evaluation in the region.

ALT	Alanine amino transferase
APRI	Aspartate-Platelet Ratio Index
AST	Aspartate
BCP	Basal core promoter or Basal core promoter
BLAST	Basic Local Alignment Search Tool
BMC	Bugando Medical Centre
cccDNA	Covalently closed circular DNA
CI	Confidence Interval
DNA	Deoxyribonucleic Acid
DR I	Direct Repeat one
DR II	Direct Repeat two
EN I	Enhancer region one
EN II	Enhancer region one
ETV	Entecavir
FBP	Full blood Picture
HBV	Hepatitis B virus
IQR	Interquartile range
IU	International unit
MUSCLE	Multiple Sequence Comparison by Log-Expectation
NCBI	National Center for Biotechnology Information
NIMR	National Institute of Medical Research
ORF	Open reading frame
pgRNA	Pre-genomic Ribonucleic Acid
PhyML	Maximum likelihood phylogenetic tree
Pol	Polymerase
PreC/C	Pre-Core/Core
PreS/S	Pre Surface/surface
RT	Reverse transcriptase
SD	Standard deviation
TDF	Tenofovir
TND	Target not detected
TZ	Tanzania
WHO	World Health Organization

Consent to publish

Not applicable, as this manuscript does not contain any individual personal data and/or media.

Competing interest

No any competing interest

Data and materials availability

All datasets generated and/or analyzed during this current study are presented in the main manuscript and are available from the corresponding author upon reasonable request. Sequences datasets generated and analysed during obtained in the current study were also submitted to GenBank and therefore available in this system with accession number from PQ446445-PQ446465.

Competing interest

None declared.

Funding

In this fund for DNA extraction was provided by Mwanza University as part of the Master’s thesis. Sequencing support was provided by the University of Mainz and the Gessen institute of virology, both from German for sequencing

Author contributions

MM, MMM, and SEM designed the work. MM, IM, and SH performed the plasma sorting and DNA extraction. BG, PK, and GS performed the amplification PCR, and Sanger sequencing. MM, BG, PK, and GS performed the sequence analysis. MMM, SEM, HJ, HAN, BRK, ARS and SBK analyzed and interpreted the data. MM, AMM and SH wrote the first draft of the manuscript, which was critically reviewed by ARS, HAN, BRK, HJ, SBK, FK, BG, PK, GS, NEN, MMM, and SEM. All the authors read and approved the final version of the manuscript.

Correspondence author

Correspondence to Mathias Mlewa (MM)

Acknowledgments

The authors would like to acknowledge the partial funding support provided by Mwanza University for this work as part of the master thesis. The authors would also like to acknowledge Mr. Teonas A. Nyalu and Barnaba Sospeter from the department of medical records, Bugando Medical Centre for their support during data extraction. I would like to give warm thanks to Mr. Henrico Shimba for the tireless laboratory mentorship he gave to make this study possible. My generous thanks go to Prof. Mirambo and Prof. Stephen E Mshana for their tireless academic training, mentorship, search for sequencing assistance and support that without them, this work would have not been done.

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A changing hepatitis B virus genetic diversity pattern in North-western Tanzania: Is it a concern for Tanzania?

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Study design, duration, area, population and sample size

Inclusion and exclusion criteria

Data and plasma samples sorting

DNA extraction, amplification, and sequence analysis

Phylogenetic analysis

Comparative phylogenetic Analysis

Preparation of the local comparative phylogenetic library

Local HBV/A comparative phylogenetic library

Local HBV/D comparative phylogenetic library

Comparative phylogenetic tree construction and annotation

Data management and analysis

Results

Patients’ social demographic and clinical data

General molecular characteristics

Phylogenetic analysis

Combined local and global comparative phylogenetic analysis for HBV/A

Combined local and global comparative phylogenetic analysis for HBV/D and HBV/G

Discussion

Conclusion

Abbreviations

Declarations

Consent to publish

Competing interest

Data and materials availability

Competing interest

Funding

Author contributions

Correspondence author

Acknowledgments

References

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