Genetic dissection of the degradation pathways for the mycotoxin fusaric acid in Burkholderia ambifaria T16.

IMPORTANCE: Fusaric acid (FA) is an important virulence factor produced by several Fusarium species. These fungi are responsible for wilt and rot diseases in a diverse range of crops. FA is toxic for animals, humans and soil-borne microorganisms. This mycotoxin reduces the survival and competition abilities of bacterial species able to antagonize Fusarium spp., due to its negative effects on viability and the production of antibiotics effective against these fungi. FA biodegradation is not a common characteristic among bacteria, and the determinants of FA catabolism have not been identified so far in any microorganism. In this study, we identified genes, enzymes, and metabolic pathways involved in the degradation of FA in the soil bacterium Burkholderia ambifaria T16. Our results provide insights into the catabolism of a pyridine-derivative involved in plant pathogenesis by a rhizosphere bacterium.

Spatial and Seasonal Variations in the Bacterial Community of an Anthropogenic Impacted Urban Stream.

Environmental changes and human activities can alter the structure and diversity of aquatic microbial communities. In this work, we analyzed the bacterial community dynamics of an urban stream to understand how these factors affect the composition of river microbial communities. Samples were taken from a stream situated in Buenos Aires, Argentina, which flows through residential, peri-urban horticultural, and industrial areas. For sampling, two stations were selected: one influenced by a series of industrial waste treatment plants and horticultural farms (PL), and the other influenced by residential areas (R). Microbial communities were analyzed by sequence analysis of 16S rRNA gene amplicons along an annual cycle. PL samples showed high nutrient content compared with R samples. The diversity and richness of the R site were more affected by seasonality than those of the PL site. At the amplicon sequence variants level, beta diversity analysis showed a differentiation between cool-season (fall and winter) and warm-season (spring and summer) samples, as well as between PL and R sites. This demonstrated that there is spatial and temporal heterogeneity in the composition of the bacterial community, which should be considered if a bioremediation strategy is applied. The taxonomic composition analysis also revealed a differential seasonal cycle of phototrophs and chemoheterotrophs between the sampling sites, as well as different taxa associated with each sampling site. This analysis, combined with a comparative analysis of global rivers, allowed us to determine the genera Arcobacter, Simplicispira, Vogesella, and Sphingomonas as potential bioindicators of anthropogenic disturbance.

Five-year microevolution of a multidrug-resistant Mycobacterium tuberculosis strain within a patient with inadequate compliance to treatment.

BACKGROUND: Whole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution -the genetic variability of M. tuberculosis at short time scales- of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported. CASE PRESENTATION: In this work, we applied whole genome sequencing analysis for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium tuberculosis isolates obtained from a patient within 57-months of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patient, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy. CONCLUSIONS: This report highlights the relevance of whole-genome sequencing analysis in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request.

Prioritisation of potential drug targets against Bartonella bacilliformis by an integrative in-silico approach.

BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.

Strategies to display heterologous proteins on the cell surface of lactic acid bacteria using as anchor the C-terminal domain of Lactobacillus acidophilus SlpA.

The surface-layer (S-layer) protein of Lactobacillus acidophilus is a crystalline array of self-assembling subunits, non-covalently bound to the most outer cell wall envelope, which constitutes up to 20% of the total cell protein content. These attributes make S-layer proteins an excellent anchor for the development of microbial cell-surface display systems. In L. acidophilus, the S-layer is formed predominantly by the protein SlpA. We have previously shown that the C-terminal domain of SlpA is responsible for the cell wall anchorage on L. acidophilus ATCC 4356. In the present study, we evaluated the C-terminal domain of SlpA of L. acidophilus ATCC 4356 as a potential anchor domain to display functional proteins on the surface of non-genetically modified lactic acid bacteria (LAB). To this end, green fluorescent protein (GFP)-CTSlpA was firstly produced in Escherichia coli and the recombinant proteins were able to spontaneously bind to the cell wall of LAB in a binding assay. GFP was successfully displayed on the S-layer stripped surface of L. acidophilus. Both the binding stability and cell survival of L. acidophilus decorated with the recombinant protein were then studied in simulated gastrointestinal conditions. Furthermore, NaCl was tested as a safer alternative to LiCl for S-layer removal. This study presents the development of a protein delivery platform involving L. acidophilus, a microorganism generally regarded as safe, which utilizes the contiguous, non-covalently attached S-layer at the cell surface of the bacterium without introducing any genetic modification.

Exploring lectin-like activity of the S-layer protein of Lactobacillus acidophilus ATCC 4356.

The surface layer (S-layer) protein of Lactobacillus acidophilus is a crystalline array of self-assembling, proteinaceous subunits non-covalently bound to the outmost bacterial cell wall envelope and is involved in the adherence of bacteria to host cells. We have previously described that the S-layer protein of L. acidophilus possesses anti-viral and anti-bacterial properties. In this work, we extracted and purified S-layer proteins from L. acidophilus ATCC 4356 cells to study their interaction with cell wall components from prokaryotic (i.e., peptidoglycan and lipoteichoic acids) and eukaryotic origin (i.e., mucin and chitin), as well as with viruses, bacteria, yeast, and blood cells. Using chimeric S-layer fused to green fluorescent protein (GFP) from different parts of the protein, we analyzed their binding capacity. Our results show that the C-terminal part of the S-layer protein presents lectin-like activity, interacting with different glycoepitopes. We further demonstrate that lipoteichoic acid (LTA) serves as an anchor for the S-layer protein. Finally, a structure for the C-terminal part of S-layer and possible binding sites were predicted by a homology-based model.

Nitrosative stress under microaerobic conditions triggers inositol metabolism in Pseudomonas extremaustralis.

Bacteria are exposed to reactive oxygen and nitrogen species that provoke oxidative and nitrosative stress which can lead to macromolecule damage. Coping with stress conditions involves the adjustment of cellular responses, which helps to address metabolic challenges. In this study, we performed a global transcriptomic analysis of the response of Pseudomonas extremaustralis to nitrosative stress, induced by S-nitrosoglutathione (GSNO), a nitric oxide donor, under microaerobic conditions. The analysis revealed the upregulation of genes associated with inositol catabolism; a compound widely distributed in nature whose metabolism in bacteria has aroused interest. The RNAseq data also showed heightened expression of genes involved in essential cellular processes like transcription, translation, amino acid transport and biosynthesis, as well as in stress resistance including iron-dependent superoxide dismutase, alkyl hydroperoxide reductase, thioredoxin, and glutathione S-transferase in response to GSNO. Furthermore, GSNO exposure differentially affected the expression of genes encoding nitrosylation target proteins, encompassing metalloproteins and proteins with free cysteine and /or tyrosine residues. Notably, genes associated with iron metabolism, such as pyoverdine synthesis and iron transporter genes, showed activation in the presence of GSNO, likely as response to enhanced protein turnover. Physiological assays demonstrated that P. extremaustralis can utilize inositol proficiently under both aerobic and microaerobic conditions, achieving growth comparable to glucose-supplemented cultures. Moreover, supplementing the culture medium with inositol enhances the stress tolerance of P. extremaustralis against combined oxidative-nitrosative stress. Concordant with the heightened expression of pyoverdine genes under nitrosative stress, elevated pyoverdine production was observed when myo-inositol was added to the culture medium. These findings highlight the influence of nitrosative stress on proteins susceptible to nitrosylation and iron metabolism. Furthermore, the activation of myo-inositol catabolism emerges as a protective mechanism against nitrosative stress, shedding light on this pathway in bacterial systems, and holding significance in the adaptation to unfavorable conditions.

Bacterial cytochrome P450s: a bioinformatics odyssey of substrate discovery.

Bacterial P450 cytochromes (BacCYPs) are versatile heme-containing proteins responsible for oxidation reactions on a wide range of substrates, contributing to the production of valuable natural products with limitless biotechnological potential. While the sequencing of microbial genomes has provided a wealth of BacCYP sequences, functional characterization lags behind, hindering our understanding of their roles. This study employs a comprehensive approach to predict BacCYP substrate specificity, bridging the gap between sequence and function. We employed an integrated approach combining sequence and functional data analysis, genomic context exploration, 3D structural modeling with molecular docking, and phylogenetic clustering. The research begins with an in-depth analysis of BacCYP sequence diversity and structural characteristics, revealing conserved motifs and recurrent residues in the active site. Phylogenetic analysis identifies distinct groups within the BacCYP family based on sequence similarity. However, our study reveals that sequence alone does not consistently predict substrate specificity, necessitating additional perspectives. The study delves into the genetic context of BacCYPs, utilizing neighboring gene information to infer potential substrates, a method proven very effective in many cases. Molecular docking is employed to assess BacCYP-substrate interactions, confirming potential substrates and providing insights into selectivity. Finally, a comprehensive strategy is proposed for predicting BacCYP substrates, involving all the evaluated approaches. The effectiveness of this strategy is demonstrated with two case studies, highlighting its potential for substrate discovery.

Omics data integration facilitates target selection for new antiparasitic drugs against TriTryp infections.

Introduction: Trypanosoma cruzi, Trypanosoma brucei, and Leishmania spp., commonly referred to as TriTryps, are a group of protozoan parasites that cause important human diseases affecting millions of people belonging to the most vulnerable populations worldwide. Current treatments have limited efficiencies and can cause serious side effects, so there is an urgent need to develop new control strategies. Presently, the identification and prioritization of appropriate targets can be aided by integrative genomic and computational approaches. Methods: In this work, we conducted a genome-wide multidimensional data integration strategy to prioritize drug targets. We included genomic, transcriptomic, metabolic, and protein structural data sources, to delineate candidate proteins with relevant features for target selection in drug development. Results and Discussion: Our final ranked list includes proteins shared by TriTryps and covers a range of biological functions including essential proteins for parasite survival or growth, oxidative stress-related enzymes, virulence factors, and proteins that are exclusive to these parasites. Our strategy found previously described candidates, which validates our approach as well as new proteins that can be attractive targets to consider during the initial steps of drug discovery.

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

INTRODUCTION: Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown. MATERIAL AND METHODS: We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina. RESULTS: We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination. DISCUSSION: Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021.

Latin America is one of the regions in which the COVID-19 pandemic has a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia, and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1,534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.

CD137 differentially regulates innate and adaptive immunity against Mycobacterium tuberculosis.

Protective immunity against Mycobacterium tuberculosis is primarily mediated by the interaction of antigen-specific T cells and antigen presenting cells, which often depends on the interplay of cytokines produced by these cells. Costimulatory signals represent a complex network of receptor-ligand interactions that qualitatively and quantitatively influence immune responses. Thus, here we investigated the function of CD137 and CD137L, molecules known to have a central role in immune regulation, during human tuberculosis (TB). We demonstrated that M. tuberculosis antigen stimulation increased both CD137 and CD137L expression on monocytes and NK cells from TB patients and healthy donors, but only up-regulated CD137 on T lymphocytes. Blockage of the CD137 pathway enhanced the levels of interferon (IFN)-γ and tumor necrosis factor (TNF)-α produced by monocytes and NK against M. tuberculosis. In contrast, CD137 blockage significantly decreased the specific degranulation of CD8(+) T cells and the percentage of specific IFN-γ and TNF-α producing lymphocytes against the pathogen. Furthermore, inhibition of the CD137 pathway markedly increased T-cell apoptosis. Taken together, our results demonstrate that CD137:CD137L interactions regulate the innate and adaptive immune response of the host against M. tuberculosis.

Selecting putative drought-tolerance markers in two contrasting soybeans.

Identifying high-yield genotypes under low water availability is essential for soybean climate-smart breeding. However, a major bottleneck lies in phenotyping, particularly in selecting cost-efficient markers associated with stress tolerance and yield stabilization. Here, we conducted in-depth phenotyping experiments in two soybean genotypes with contrasting drought tolerance, MUNASQA (tolerant) and TJ2049 (susceptible), to better understand soybean stress physiology and identify/statistically validate drought-tolerance and yield-stabilization traits as potential breeding markers. Firstly, at the critical reproductive stage (R5), the molecular differences between the genotype's responses to mild water deficit were explored through massive analysis of cDNA ends (MACE)-transcriptomic and gene ontology. MUNASQA transcriptional profile, compared to TJ2049, revealed significant differences when responding to drought. Next, both genotypes were phenotyped under mild water deficit, imposed in vegetative (V3) and R5 stages, by evaluating 22 stress-response, growth, and water-use markers, which were subsequently correlated between phenological stages and with yield. Several markers showed high consistency, independent of the phenological stage, demonstrating the effectiveness of the phenotyping methodology and its possible use for early selection. Finally, these markers were classified and selected according to their cost-feasibility, statistical weight, and correlation with yield. Here, pubescence, stomatal density, and canopy temperature depression emerged as promising breeding markers for the early selection of drought-tolerant soybeans.

Pathway Driven Target Selection in Klebsiella pneumoniae: Insights Into Carbapenem Exposure.

Carbapenem-resistant Klebsiella pneumoniae (CR-KP) represents an emerging threat to public health. CR-KP infections result in elevated morbidity and mortality. This fact, coupled with their global dissemination and increasingly limited number of therapeutic options, highlights the urgency of novel antimicrobials. Innovative strategies linking genome-wide interrogation with multi-layered metabolic data integration can accelerate the early steps of drug development, particularly target selection. Using the BioCyc ontology, we generated and manually refined a metabolic network for a CR-KP, K. pneumoniae Kp13. Converted into a reaction graph, we conducted topological-based analyses in this network to prioritize pathways exhibiting druggable features and fragile metabolic points likely exploitable to develop novel antimicrobials. Our results point to the aptness of previously recognized pathways, such as lipopolysaccharide and peptidoglycan synthesis, and casts light on the possibility of targeting less explored cellular functions. These functions include the production of lipoate, trehalose, glycine betaine, and flavin, as well as the salvaging of methionine. Energy metabolism pathways emerged as attractive targets in the context of carbapenem exposure, targeted either alone or in conjunction with current therapeutic options. These results prompt further experimental investigation aimed at controlling this highly relevant pathogen.

Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway of Leishmania Species.

Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases' participation in protein-protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

Isolation and Characterization of vB_MsmS_Celfi: A New Mycobacterium tuberculosis Bacteriophage.

Introduction: Because of the clinical relevance of Mycobacteria, and from a therapeutic perspective, there is an increasing interest to study phages that infect bacteria belonging to this genus. Materials and Methods: A phage was isolated from a soil sample, using Mycobacterium smegmatis as host. Its characterization included sequencing, annotation, and analysis of the genome, host range determination, and electron microscopy imaging. Results: Mycobacterium phage vB_MsmS_Celfi is a temperate phage able to infect Mycobacterium tuberculosis with high efficiency. From electron microscopy images, Celfi belongs to the Siphoviridae family. Genome analysis classified phage Celfi into cluster L, subcluster L2 of Actinobacteriophage clusters. Mycobacterium phage Celfi exhibits a Lysin B distant to those present in other members of the subcluster and other mycobacteriophages. Conclusions: The discovery of new phages that infect M. tuberculosis could contribute to the development of novel tools for detection systems and future treatment of the disease.

Genome Sequence and Characterization of Lactobacillus casei Phage, vB_LcaM_Lbab1 Isolated from Raw Milk.

Introduction: Only a few Lactobacillus casei phages have so far been characterized. As several L. casei strains are part of probiotic formulations, bacteriophage outbreaks targeting these strains can lead to critical losses within the dairy industry. Materials and Methods: A new L. casei phage was isolated from raw milk obtained from a milking yard from the province of Buenos Aires. The phage genome was sequenced, annotated, and analyzed. Morphology was determined by electron microscopy and the host range was established. Results: Lactobacillus phage vB_LcaM_Lbab1 is a member of the Herelleviridae family and features a host range including L. casei/Lactobacillus paracasei and Lactobacillus kefiri strains. We further analyzed the baseplate proteins in silico and found putative carbohydrate binding modules that are responsible for host recognition in other Lactobacillus phages. Conclusions: A new Lactobacillus phage was isolated and characterized. The focus was made on its host recognition mechanism, pointing toward the development of future strategies to avoid deleterious infections in the dairy industry.

From Genome to Drugs: New Approaches in Antimicrobial Discovery.

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

Cost-Effective Method to Perform SARS-CoV-2 Variant Surveillance: Detection of Alpha, Gamma, Lambda, Delta, Epsilon, and Zeta in Argentina.

SARS-CoV-2 variants with concerning characteristics have emerged since the end of 2020. Surveillance of SARS-CoV-2 variants was performed on a total of 4,851 samples from the capital city and 10 provinces of Argentina, during 51 epidemiological weeks (EWs) that covered the end of the first wave and the ongoing second wave of the COVID-19 pandemic in the country (EW 44/2020 to EW 41/2021). The surveillance strategy was mainly based on Sanger sequencing of a Spike coding region that allows the identification of signature mutations associated with variants. In addition, whole-genome sequences were obtained from 637 samples. The main variants found were Gamma and Lambda, and to a lesser extent, Alpha, Zeta, and Epsilon, and more recently, Delta. Whereas, Gamma dominated in different regions of the country, both Gamma and Lambda prevailed in the most populated area, the metropolitan region of Buenos Aires. The lineages that circulated on the first wave were replaced by emergent variants in a term of a few weeks. At the end of the ongoing second wave, Delta began to be detected, replacing Gamma and Lambda. This scenario is consistent with the Latin American variant landscape, so far characterized by a concurrent increase in Delta circulation and a stabilization in the number of cases. The cost-effective surveillance protocol presented here allowed for a rapid response in a resource-limited setting, added information on the expansion of Lambda in South America, and contributed to the implementation of public health measures to control the disease spread in Argentina.