## 1 Introduction  
Proteomics workflows start with sample preparation, which involves extracting and solubilizing proteins from complex sources such as mammalian cells, bacterial samples, or biological fluids like plasma or serum. The standard protocol then proceeds with steps such as denaturation, reduction and alkylation of cysteine residues, and enzymatic digestion [1, 2]. Complex proteomic samples are commonly prepared using in-solution digestion by proteases, such as trypsin or Lys-C, in the presence of urea as a chaotropic agent [3, 4]. This approach is simpler, more scalable, and less time-consuming compared to in-gel digestion. Some variations for in-solution digestion utilize buffers with minimal surfactant concentrations, like SDS [5] or SDC [6, 7]. Urea or detergents help solubilize proteins, enhancing digestion efficiency and peptide yield. However, SDS and urea are incompatible with LC-MS/MS, requiring an additional step to reduce their concentration before downstream analysis by mass spectrometry. [PERSON] et al. [8] developed a protocol for clean sample preparation through trypsinolysis of protein suspension in ammonium bicarbonate, avoiding the use of detergents and chaotropic agents. In this study, this protocol was applied to prepare complex samples from HEK293T or CHO cells, _Escherichia coli_, and human plasma. CHO cells and _E. coli_ lines were selected because they are extensively utilized in the biopharmaceutical industry for the production of recombinant proteins [9; 10]. The inclusion of plasma as the third focus of study stems from its significance as a valuable source of information about human health in clinical practice [11]. Moreover, all three sample types are readily accessible and commonly available for research in most laboratories. Liquid chromatography-tandem mass-spectrometry LC-MS/MS has become the most powerful method for protein identification and quantification [12]. Most proteomics data today are generated using a data-dependent acquisition (DDA) approach, in which the most intense precursor ions are selected for subsequent MS/MS fragmentation [13; 14]. The analysis of output data from these instruments using Mascot or other proteomic tools [15; 16; 17] provides detailed information about the protein composition of biological samples. The results are typically presented as summary reports or output tables containing a total number of identifications, protein identifiers, scores, sequence coverage, false discovery rate (FDR), and other relevant data. The number of protein identifications is a crucial metric, influenced by factors such as the sample preparation protocol, LC conditions (e.g., column/gradient length, sorbent particle/pore sizes), and MS acquisition settings (e.g., spectra rate, \(m/z\) range, and other parameters) [18]. Additionally, the number of identifications is affected by the type and complexity of the biological samples and variations in protein distribution. This study aimed to optimize conditions to increase the number of protein identifications in DDA mode without sacrificing the throughput of the method. One key parameter for achieving this is the gradient time in liquid chromatography (LC). It is well established that lengthening the LC gradient can enhance protein identification rates [19]. Some studies report using very long gradients, up to 10 h, to achieve maximum peptide separation [20]. The efficiency of peptide separation, which enhances protein identification, is often estimated by peak capacity. However, peak capacity does not increase proportionally with gradient time; rather, it tends to plateau at extended gradient durations [21; 22]. Moreover, longer gradients significantly reduce analysis productivity, especially when dealing with more samples. Therefore, alternative approaches are required to implement a more detailed proteomic analysis of complex samples without extending analysis time. One effective strategy is to increase the spectral acquisition rate in tandem mass spectrometry and use advanced software for raw data analysis.