Chakib Nejjari

Lagoons are fragile marine ecosystems that are considerably affected by anthropogenic pollutants. We performed a spatiotemporal characterization of the microbiome of two Moroccan lagoons, Marchica and Oualidia, both classified as Ramsar sites, the former on the Mediterranean coast and the latter on the Atlantic coast. We investigated their microbial diversity and abundance using 16S rRNA amplicon- and shotgun-based metagenomics approaches during the summers of 2014 and 2015. The bacterial microbiome was composed primarily of Proteobacteria (25–53%, 29–29%), Cyanobacteria (34–12%, 11–0.53%), Bacteroidetes (24–16%, 23–43%), Actinobacteria (7–11%, 13–7%), and Verrucomicrobia (4–1%, 15–14%) in Marchica and Oualidia in 2014 and 2015, respectively. Interestingly, 48 strains were newly reported in lagoon ecosystems, while eight unknown viruses were detected in Mediterranean Marchica only. Statistical analysis showed higher microbial diversity in the Atlantic lagoon than in the Mediterranean lagoon and a robust relationship between alpha diversity and geographic sampling locations. This first-ever metagenomics study on Moroccan aquatic ecosystems enriched the national catalog of marine microorganisms. They will be investigated as candidates for bioindication properties, biomonitoring potential, biotechnology valorization, biodiversity protection, and lagoon health assessment.

The aim of this study was to investigate the relationship between meteorological parameters, air quality and daily COVID-19 transmission in Morocco. We collected daily data of confirmed COVID-19 cases in the Casablanca region, as well as meteorological parameters (average temperature, wind, relative humidity, precipitation, duration of insolation) and air quality parameters (CO, NO₂, 03, SO₂, PM10) during the period of 2 March 2020, to 31 December 2020. The General Additive Model (GAM) was used to assess the impact of these parameters on daily cases of COVID-19. A total of 172,746 confirmed cases were reported in the study period. Positive associations were observed between COVID-19 and wind above 20 m/s and humidity above 80%. However, temperatures above 25° were negatively associated with daily cases of COVID-19. PM10 and O₃ had a positive effect on the increase in the number of daily confirmed COVID-19 cases, while precipitation had a borderline effect below 25 mm and a negative effect above this value. The findings in this study suggest that significant associations exist between meteorological factors, air quality pollution (PM10) and the transmission of COVID-19. Our findings may help public health authorities better control the spread of COVID-19.

While students in the health sciences occupy pivotal roles in the Moroccan COVID-19 response and vaccination campaigns, factors associated with COVID-19 vaccine acceptability among students have not been reported. This study aimed to determine the willingness and identify predictive attitudes and beliefs of COVID-19 vaccine acceptance among health science students in Morocco. A cross-sectional, self-administered online questionnaire was conducted among students of the Mohammed VI University of Health Sciences in Casablanca, Morocco in January 2021. In total, 1272 students participated. Univariate and multivariate logistic regression models were used to calculate odds ratios and 95% confidence intervals. Overall, 26.9% of participants reported being willing to receive the COVID-19 vaccine. Between genders, male students were more likely to accept the vaccine. Regarding individual attitudes and beliefs about COVID-19 infection, students with greater confidence in COVID-19 information, and higher perceived likelihood and perceived severity of infection were more likely to be willing to get the vaccine. Concerning a COVID-19 vaccine, students who reported lower levels of perceived harm and higher levels of perceived vaccine effectiveness were more willing to get vaccinated. Our findings help guide future efforts to tailor communication and identify strategies to increase COVID-19 vaccine uptake among students.

The COVID-19 pandemic has been ongoing since its onset in late November 2019 in Wuhan, China. Understanding and monitoring the genetic evolution of the virus, its geographical characteristics, and its stability are particularly important for controlling the spread of the disease and especially for the development of a universal vaccine covering all circulating strains. From this perspective, we analyzed 30,983 complete SARS-CoV-2 genomes from 79 countries located in the six continents and collected from 24 December 2019, to 13 May 2020, according to the GISAID database. Our analysis revealed the presence of 3206 variant sites, with a uniform distribution of mutation types in different geographic areas. Remarkably, a low frequency of recurrent mutations has been observed; only 169 mutations (5.27%) had a prevalence greater than 1% of genomes. Nevertheless, fourteen non-synonymous hotspot mutations (>10%) have been identified at different locations along the viral genome; eight in ORF1ab polyprotein (in nsp2, nsp3, transmembrane domain, RdRp, helicase, exonuclease, and endoribonuclease), three in nucleocapsid protein, and one in each of three proteins: Spike, ORF3a, and ORF8. Moreover, 36 non-synonymous mutations were identified in the receptor-binding domain (RBD) of the spike protein with a low prevalence (<1%) across all genomes, of which only four could potentially enhance the binding of the SARS-CoV-2 spike protein to the human ACE2 receptor. These results along with intra-genomic divergence of SARS-CoV-2 could indicate that unlike the influenza virus or HIV viruses, SARS-CoV-2 has a low mutation rate which makes the development of an effective global vaccine very likely.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new infectious disease that first emerged in Hubei province, China, in December 2019. On 2 March 2020, the Moroccan Ministry of Health confirmed the first COVID-19 case in Morocco. The new virus SARS-CoV-2 was identified in the sample of a Moroccan expatriate residing in Italy. Without a therapeutic vaccine or specific antiviral drugs, early detection and isolation become essential against novel Coronavirus. This study aims to analyze the epidemiological profile of the SARS-CoV-2 in Moroccan cases and to investigate the dynamic of RdRp, N , and E genes in patients from diagnosis until the recovery. Among 859 COVID-19 RT-PCR tests realized for 376 patients, 187 cases had positive results COVID-19. 4% were positive with the 3 genes RdRp, N , and E , 40 % with N and E genes, 3% with RdRp and N genes, 31% with only the RdRp gene and 22% cases are positives with N gene. The analysis of the Covid-19 genes ( RdRp, N , and E ) dynamic reveal that more than 6% stay positive with detection of the N and E gene, and 14% with the N gene after 12 days of treatment. The median period from positive to the first negative Covid-19 RT-PCR tests was 6.8±2.24 days for 44% cases, 14.31± 2.4 days for 30%, and 22.67 ± 1.21 days for 4%. This a first description of the Moroccan COVID-19 cases and the analysis of the dynamic of the RdRp, N , and E genes. The analysis of our population can help to improve in the care of patients.

In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variant sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 38 recurrent non-synonymous mutations, including ten hotspot mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed certain genotypes specific to the geographic location. We also found co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2. On the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets We have also created an inclusive unified database ( http://genoma.ma/covid-19/ ) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.