Population structure of the seahorse Hippocampus reidi in two Brazilian estuaries

This study aimed to evaluate and compare seasonal variations of Hippocampus reidi population structures in two Brazilian coastal areas. Samples were collected from the rocky shores of Urca and Duas Irmãs Island by freediving along fixed transects. All seahorses observed in the study were recorded, measured, and identified by sex and reproductive stage. Seahorse behavior and fish depth were also registered. All individuals were photo-identified to estimate recapture rates. Holdfast used by seahorses was also recorded. Results showed low densities at both sites; sex ratio and juvenile/adult proportion did not appear to vary with season. The seahorse height differed between the two areas but did not vary with season nor sex. Seahorses in both sites were found in shallow waters (i.e. up to 4 meters), and the depth did not vary by season nor sex. Males were more frequently recaptured than females in both areas. All seahorses were reproductively active year-round, peaking at rainy periods in both areas. The seahorses were more often recorded while resting and seemed to anchor on seaweed. Though in different bays, seahorse population structure and seasonality appeared similar. These data provide useful baseline data for future population assessments. Abstract

INTRODUCTION
Estuaries provide many ecological functions for inhabiting organisms such as nurseries, refuges, foraging sources, migration areas, and reproduction sites (Gibson, 1994;Koutsikopoulos et al., 1989;Miller, et al., 1985;Vasconcelos et al., 2011). These ecological functions are extremely important, mainly to estuarine fish, as some species rely on these environments throughout their whole life cycle.
Teleost fish in temperate estuaries, where environmental variation is broader and more seasonal, generally show seasonal patterns of growth, reproduction, abundance, and density (Blaber, 2000;Elliott and Hemingway, 2002). Consequently, fish species can adapt to reach desirable reproduction and recruitment conditions, with adjustments in populations such as density, sex ratio, juvenile abundance, residence time, and height class curve. Although water parameters may drive biological responses, biotic trends may also play an important role for the species (Power, 2000;Power et al., 2000Power andAttrill, 2002, 2003). Food and habitat availability, competition, and predation can also be important to explain and predict the temporal and spatial patterns of estuarine organisms (Ogburn-Matthews and Allen, 1993;Lankford and Targett, 1994;Barry et al., 1996). The relationship between the biota distribution with biotic and abiotic factors in estuaries have received considerable attention (Akin et al., 2005;Kotta et al., 2015;Conroy et al., 2017;Newcomer et al., 2018;Grimaldo et al., 2020). These studies focused on fish population and community patterns in this ecosystem and are one of the most dominant groups (Blaber and Blaber, 1980;Marshall and Elliott, 1998;Whitfield, 1999;Akin et al., 2005;Grimaldo et al., 2020).
Seahorses are coastal fish which inhabit shallow water in tropical and temperate areas (Lourie et al., 1999). Of the 46 seahorse species worldwide, seven are found in estuaries (Correia et al., 2018;Correia et al., 2015;Lourie et al., 1999;Harasti et al., 2012), of which Hippocampus capensis is exclusively estuarine (Claassens et al., 2020). Species of temperate estuaries, such as Hippocampus guttulatus, have an intense response to seasonal variation of environmental conditions, particularly temperature (Correia et al., 2018), as do Hippocampus reidi in tropical estuaries, reproducing mostly in the dry windy season (Mai and Velasco, 2012). In Brazil, three species are commonly found in ecosystems near rocky reefs, mangroves, and coral reefs (Rosa et al., 2007;Freret-Meurer and Andreata, 2008;Mai and Rosa, 2009;Freret-Meurer et al., 2018a, b). The longsnout seahorse Hippocampus reidi Ginsburg, 1933 is the most common along the Brazilian coast and is currently rated Vulnerable in the Brazilian red list of the Brazilian Ministry of Environment (ICMBIO, 2018) and Near Threatened globally (Oliveira and Pollom, 2017).
Tracking and understanding seahorse population structure dynamics, especially in regional estuaries, is extremely important. This can help evaluate the effect of environmental changes on population and even help develop regional conservation estuary policy. These organisms generally exhibit patchy distribution, low mobility, and small home ranges Caldwell and Vincent 2012), leaving their populations vulnerable to decline or even eradication.
There are some studies on H. reidi populations in Brazil (Dias and Rosa, 2003;Rosa et al., 2005;Rosa et al., 2007;Mai and Velasco, 2012;Aylesworth et al., 2015;Freret-Meurer et al., 2018a, b). These focused on the environment and certain aspects of population structure. However, none of them hypothesized on seasonal population variation, extremely important in estuaries due to their dynamics.
The present work seeks to investigate the effect of seasonal estuarine trends (salinity and temperature) on the longsnout seahorse H. reidi population structure in two estuaries in the state of Rio de Janeiro, Brazil. We expected to find (1) similar overall water physical and chemical factors in these two areas; (2) a difference in environmental conditions in accordance with dry and rainy seasons; and (3) similar habitats and seasonal structures among seahorse populations.

METHODS
This study was conducted with the permission of the Chico Mendes Institute for Biodiversity Conservation (ICMBio) (permit number 44409-3). Data collection was conducted at two coastal rocky shore locations in Rio de Janeiro: Urca beach (U) (22°56'33" S -43°09'27" W), located on the west side of Guanabara Bay, and Duas Irmãs island (DI), located in Sepetiba Bay (22°56'38" S, 43°57'46" W; Figure 1). The two factors that helped determine these locations were the presence of H. reidi and water visibility, crucial for data accuracy.
Urca beach is located in Guanabara Bay, which has an area of 380km² (Kjerfve et al., 1997). The bay is 84% shallow water (up to 10 m in depth), though some areas reach 40 m in depth, as recorded by the central channel (Figueiredo et al., 2014). Mean rainfall during the rainy and dry seasons varies between 3 mm -85 mm and 80 mm -110mm, respectively (INMET, 1992). Urca beach is at the entrance channel of the bay and is considered a tourist site. It has a rocky reef composed of a diverse range of holdfast (Sola and Paiva, 2001). Seahorse populations had previously been recorded at the site. Seahorse population structure in two estuaries Fernández do Carmo et al.
Temperature and salinity were measured monthly with a mercury thermometer and a refractometer, respectively, on the water surface. Monthly cumulative rainfall data were drawn from the National Institute of Meteorology (INMET) to categorize seasons into rainy (October to March) and dry (April to September) periods for further seasonal analyses.
Seahorse individuals were counted during transects for abundance and density estimates. Further, seahorse sex was determined by the presence of brood pouches (males) or their absence (females) (Lourie, Vincent and Hall, 1999).
All seahorses were photographed using a Nikon AW300 for individual identification and further recapture analysis (Freret-Meurer et al., 2013), using I3S Classic version 4.02 software. The Constancy Index (CI) (adapted from Dajoz, 1983) was calculated to categorize as follows for each recaptured individual: rare (CI < 25%), visitors (25% < CI < 50%), and constant (CI > 50%) (Freret-Meurer and Andreata, 2008). A Jolly-Seber stochastic model for open populations (Jolly, 1965; Duas Irmas island is Sepetiba bay, which has a surface area of approximately 305 km² and depth ranging between 8.6 meters and 30 meters (Fonseca, 1978). Annual rainfall values range between 1,000mm and 2,100 mm (Barbieri and Kronemberger 1994). The two beaches are surrounded by rocky shores. Like Urca Beach, it is also a tourist site. Duas Irmãs island was chosen due to previous bibliographic research about local benthic characteristics, which led us to believe that it could offer seahorse habitats as it is surrounded by rocky reefs with seaweed, bryozoans, and porifera (Széchy et al., 2005).
Local seahorse population was monitored monthly through snorkeling between February 2018 and January 2019. During dives, four fixed 20 m x 4 m (total of 320 m²) transects were conducted, for an effective search time of 90 minutes per dive along the rocky shores (Freret-Meurer et al., 2018a). Maximum survey site depth was 4 cm in both areas. A total of 96 transects were performed, and 36 diving hours were spent on surveys. Fernández do Carmo et al. Seber, 1982) was used to estimate population size, assuming the same capture probability for marked and unmarked animals. The model formula was computed using MS Excel.
Height and depth of occurrence were also measured underwater. Seahorse height was measured as a straight line from the coronet top to the prehensile tail end (Lourie, 2003). Individuals with a brood pouch and cloaca smaller than 56 mm were considered juveniles (Freret-Meurer et al., 2018a).
We recorded the holdfasts where seahorses were anchored. Holdfasts were identified in the field, but samples were collected and taken to the laboratory for further analysis when identification difficulties were encountered, according to Brusca et al. (2018), Muricy and Hajdu (2006), and Joly (1967). The holdfasts were classified at the species levels or higher taxonomic groups. The allochthonous holdfast was classified as a holdfast from other ecosystems and artificial as anthropogenic holdfasts.
The differences in sex ratio and the juvenile/ adult proportion between seasons for each area were analyzed using the Chi-Squared test. Seasonal variations of seahorse height and depth of occurrence were checked by paired Student's T-test in GraphPad InStat 3.0, and a Kolmogorov-Smirnov test was used to confirm normal distribution for heights and anchorage depth. Student's tests were also used to calculate the difference between sex among these two measurements. In addition, the frequency of occurrence (FO) was calculated to infer the association with the holdfast, and a Shannon-diversity index was used to evaluate the holdfast association diversity.
Two-way permutational analysis of variance (PERMANOVA; Anderson, 2005) was applied to test for density differences, precipitation, temperature, and salinity between beaches (Urca Beach and Duas Irmãs Island) and periods (dry and rainy) using CANOCO 5.0 software. A mixed model was used to deal with spatial pseudoreplication (Anderson et al., 2008), where the rainy and dry periods were used as fixed and orthogonal factors and sampling period as a random factor. The Bray-Curtis distance was used in PERMANOVA, and data was permuted 9,999 times per analysis.
A total of 66 seahorses were found at Urca Beach and 52 at Duas Irmãs Island, resulting in an average monthly abundance of 6 ± 1 individuals/ month and 4 ± 2 individuals/month respectively. The mean seahorse density was higher at Urca Beach than at Duas Irmãs Island (Table 1 and Figure 3).
At both sites, males were more frequently resighted than females. At Urca Beach, re-sights were 7% for females and 17% for males. At Duas Irmãs Island, results were 24% for females, 31% for males, and 50% for juveniles. Annual re-sight rates were 11% at Urca Beach and 29% at Duas Irmãs Island. One female was re-sighted six times at Urca Beach, while one male was re-sighted five times at Duas Irmãs Island. The other individuals were re-sighted less than four times in each area. Per the Constancy Index, individuals from Urca Beach were considered rare (n=4) and visitors (n=3). Those from Duas Irmãs Island were deemed rare (n=11) and visitors (n=3). There were no resident seahorses in either area.
The Jolly-Seber model suggested a possible population of 236 individuals at Urca Beach and 140 at Duas Irmãs Island.
Seahorse depths differed between periods at both sites (t Urca = 3.54, p = 0.001; t Duas irmãs = 2.90, p = 0.005), with greater depth recorded during rainy periods at Urca Beach and dry period at Duas Irmãs Island (Table 1). Depth showed a different pattern by sex and study site. Both females and males were found significantly deeper during the rainy season at Urca Beach (t= 2.6, p= 0.02; t= 2.0, p= 0.08, respectively), while only females showed a significant difference between periods (t = 2.3, p= 0.04) at Duas Irmãs Island, where males recorded t = 1.5 and p= 0.1. Despite the difference between periods, there was no significant difference in depth of occurrence between male and females in either area (t Urca = 0.06, p = 0.90; t Duas irmãs = 0.20, p = 0.90) (Table1). The mean depths were 1.52 m ± 0.02 m and 2.27 m ± 0.04 m at Urca Beach and Duas Irmãs Island, respectively.
Most seahorses were found in stages 0, 2, and 3, representing reproductive activity year-round, Seahorse population structure in two estuaries Fernández do Carmo et al.

Figure 6. Length classes (mm) of the seahorses H. reidi according to rainy and dry seasons (a) and length class (mm) on Urca beach (b); Length classes (mm) of the seahorses H. reidi according to rainy and dry seasons (c) and length class (mm) on Duas Irmãs island (d).
peaking during rainy periods in both areas. Both populations exhibited different behaviors, such as courting, swimming, foraging, and resting. Courting and swimming were observed only at Urca Beach (5%, 2% respectively). Foraging was observed in only 2% of seahorses, and the most observed behavior were resting (>90%) in both areas.
On the other hand, seahorses from Duas Irmas Island were frequently anchored to the cnidarian Carijoa riisei (Duchassaing and Michelotti, 1860) (FO = 48%) and to the turf seaweed (FO = 19%). However, juveniles were only recorded on C. riisei and on seaweed Acanthophora sp. (J.V.Lamouroux, 1813). Cnidaria and seaweed were the two taxonomic groups most used at Duas Irmãs Island. Urca Beach had a higher holdfast association diversity (H' = 2.38) than Duas Irmãs Island (H'=1.52) (Figure 7b). The holdfast species where seahorses were found are listed in the Supplementary Materials (Table S1 and Table S2).

DISCUSSION
This study highlights a pattern in the population structure of both seahorse populations associated with rocky reefs in different bays within Rio de Janeiro State, suggesting stability in the yearround population structure predictions. In fact, the stability of population parameters of fish tends to disagree with the well-marked dry and rainy seasons (Castillo-Rivera, 2013, Qin et al., 2017, as observed in the present study. Both study sites were characterized by low precipitation, low temperature, and high salinity during the dry season, as well as high precipitation, high temperature, and lower salinity during the rainy season. Estuarine fish tend to be broadly tolerant to physical and chemical factors of water, especially temperature and salinity, as documented  by various authors (Allen and Horn, 1975;Hoff and Ibara, 1977;Weinstein, Weiss and Walters, 1980;Loneragan et al., 1987;Peterson and Ross, 1991;Marshall and Elliot, 1998;Araujo, Bailey and Williams, 1999). These serve as prime environmental factors which directly and indirectly affect species association patterns in these ecosystems (Horn and Allen, 1978;Monaco, Lowery and Emmett, 1992;Emmett et al., 2000). Similarly reported in the study of Hippocampus mohnickey, which seasonal variations in temperature drives migrations in and out of the estuary (Qin et al., 2017).
In our study, neither salinity nor temperature differed statistically between areas, which could explain the similar pattern in the seahorse population structure. However, they did vary between seasons, which could influence migration and changes in population structure. Still, no significant changes were recorded in our study, corroborating Schwarz et al. (2021) and Mai and Velasco (2012), who studied H. reidi in an estuary in northeastern Brazil. In addition, rainfall plays an important role in estuaries (Mendoza et al., 2002), as does mediating fish abundance seasonality, where higher abundances were often recorded during rainy periods (Castillo-Rivera, 2013). In the present study, seahorse abundance and density did not appear to be affected by rainfall. The same was noted for salinity and temperature variations. A possible explanation is that H. reidi occurs in a variety of environments along the Brazilian coast, including mangroves (Mai and Velasco, 2012), open water rocky shores (Freret-Meurer and Oliveira, 2012;Freret-Meurer et al., 2018b), and hypersaline areas (Rosa et al., 2007). In addition, according to Tseng et al. (2020), high temperatures (>30°C) had a direct effect on the survival of Seahorse population structure in two estuaries Fernández do Carmo et al. this seahorse species, and they can survive within a salinity range of 15-34 g/kg, suggesting high tolerance to physical and chemical water factors.
The long-snout seahorse exhibited low density and patchy distribution, a pattern similar to other species , Rosa et al., 2007, Siqueira et al., 2017, Freret-Meurer et al., 2018a. The density of longsnout seahorse H. reidi varied along the Brazilian coast between 0.0023 to 0.066 fish/m² (Rosa et al., 2007), lower than recorded in the present study. However, though low density is a group characteristic of seahorse populations, some studies have reported higher densities, such as Freret-Meurer et al., 2018a (0.21 ± 0.11 ind. m -2 ) and Schwarz et al., 2021 (0 to 0.32 fish/ m2). Low densities are often found for several other seahorse species, such as Hippocampus hippocampus in Ria Formosa lagoon and on Chalkidiki Peninsula (ranging between 0.05 ind.m -2 and 0.015 ind.m -2 ), in the North Aegean Sea (Correia et al., 2015;Correia et al., 2020). Mean densities of 0.0089 m -2 are observed for Hippocampus capensis in South Africa (Bell et al., 2003).
In addition to density, another population attribute analyzed was sex ratio, which was found not to change seasonally. Our finding corroborated other studies, such as for H. comes in the Philippines (Perante et al., 2002) and H. reidi in Rio de Janeiro (Freret-Meurer et al., 2018a). Seasonal changes in this attribute have been reported for Hippocampus zostera (Strawn, 1958) and Hippocampus abdominalis (Martin-Smith and Vincent, 2005), suggesting that sex ratios can vary according to seahorse species. It is also important to consider that females tend to have wider home ranges (Freret-Meurer and Andreata, 2008), which could explain the skew for larger male recapture rates in this study.
The adult proportion was greater than juveniles in this study, with no seasonal variation. The absence of seasonality was expected due to the year-round reproduction of the species (Freret-Meurer et al., 2018a). Low juvenile proportions in relation to adults were also documented for the same and other seahorse species, such as H. guttulatus (Correia et al., 2015), H. capensis (Lockyear et al., 2006), andH. reidi (Freret-Meurer et al., 2018).
The H. reidi height was consistent with the range generally found for the species (Lourie et al., 2004;Rosa et al., 2007;Aylesworth et al., 2015;Freret-Meurer et al., 2018a), but diverged between beaches; seahorses were larget at Urca Beach than at Duas Irmãs Island. The seahorse H. reidi height can vary along the Brazilian coast, such as in the Northeast (Rosa et al., 2007;Silveira, 2011) and on coastal rocky reefs from Rio de Janeiro (Freret-Meurer et al., 2018b), where the species is larger than observed in our study.
In the present study, H. reidi occurred in shallow areas, most likely due to the maximum depth of 4 meters recorded at the surveyed rocky shores. The longsnout seahorse has been found at 10 cm (Rosa et al., 2002) and 55 m (Vari, 1982). Further, it may appear in different setting types between sites, as reported by Freret-Meurer et al. (2018a), who found H. reidi in shallow waters (1.2m) and in an estuary rocky reef with maximum depth of 3m. This is in contrast with Oliveira and Freret-Meurer (2012), who reported larger abundances in deeper waters (5 m) in Arraial do Cabo, where the rocky bottom depth was 9 m; the occurrence depth of seahorses may also be related to the depth of the rocky shore. In addition to the results found in this study, shallow waters could provide better refuge and shelter (Wallace and Van Der Elst, 1975;Blaber, 1985) from possible predators that are more commonly found in deeper waters (Whitfield and Blaber, 1978). Seahorse depth of occurrence differed between periods in both areas. This could be due to holdfast availability, which changes between periods at Duas Irmãs Island (Amado Filho et al., 2003) and Urca Beach (Breves-Ramos et al., 2005). There is evidence that holdfast availability and seahorse depth of occurrence could be correlated, as seen for H. whitei which aggregate in seagrass beds in shallow areas (Manning et al., 2018). Manning et al. (2018) also suggest that this correlation could offer spatial differences in feeding and reproductive opportunities.
The seahorses exhibited reproductive stages throughout the year with peaks during rainy  (Correia et al., 2018); this suggests H. reidi tolerance to water physical and chemical variables. Other behaviors were also observed, mainly resting, which is characteristic of Syngnathidae (Lourie, Vincent and Hall, 1999;Freret-Meurer, Andreata and Alves, 2012). This behavior is characterized by the seahorse anchored with their bodies close to the holdfast, as also described for H. capensis (Bell et al., 2003) and H. abdominalis (Martin-Smith and Vincent, 2005).
Urca Beach exhibited a higher diversity of anchorage points, but also a higher seahorse abundance, which could have influenced the results. Urca Beach is also generally calm and protected from wave exposure, whereas Duas Irmãs Island is more exposed and experiences higher hydrodynamic conditions during certain periods. This could influence the occurrence of certain holdfasts. In both sites, seahorses were frequently found on different seaweed species, suggesting that future approaches applying morphofunctional groups for testing holdfast use could be of interest.
Both population sizes seemed small compared to other seahorse populations, as was reported for H. guttulatus in Thau lagoon (Riquet et al., 2019) with an estimate of 2,742 individuals. In addition, a recent study reported an estimated population of 28,763 individuals for the Knysna seahorse Hippocampus capensis in Africa (Mkare et al., 2021). The most similar data to our study was reported for Hippocampus whitei in Port Stephens, Australia, with 213 individuals (Harasti et al., 2012). Our data should be carefully considered for estimated population size due to the small study area. They represent local population data and should be used with caution as a baseline for estimated seahorse population size in both bays.
Population structures of H. reidi in both study sites resemble each other in aspects such as height, depth of occurrence, and holdfast use. Moreover, the factors analyzed do not seem related to their density nor population structure. This species is found mostly in resting behavior and during reproductive periods throughout the year, with peaks during rainy periods. The low recapture rates could indicate that these areas work as a passage area, maybe to inner bay regions. These seasonal movements had already been reported for Hippocampus mohnikei Bleeker, 1853 on the Chinese coast, moving to the inner bay during summer (Qin et al., 2017). Also supporting these facts, Faro and Bonecker (2000) recorded seahorse fryes in the innermost part of Guanabara Bay (Rio de Janeiro), indicating a possible reproduction or nursery area. Seaweed was the most used holdfast for anchorage, highlighting the significance of the phytal ecosystems for seahorses.
Our results indicate that both bays shelter a population of the longsnout seahorse H. reidi with a stable structure year-round, despite a low abundance; these require further study and protection.


Independent case-control study in KCNJ11 gene polymorphism with Type 2 diabetes Mellitus

Background Type 2 Diabetes Mellitus (T2DM) is the most common form of diabetes in the aging population. This chronic metabolic disorder has discovered many candidate genes, and KCNJ11 was one of the genes associated with insulin secretion pathways mediated by potassium channels. There have been limited studies on the rs5210 polymorphism in T2DM patients, and none of them have been conducted in Saudi Arabia. Aim The aim of this study is to investigate at genotyping levels of rs5210 polymorphism in the KCNJ11 gene in older population with T2DM in the Saudi Population. Methods Based on the sample size design, this case-control study included 102 T2DM cases and 102 controls. Using the PCR-RFLP assay, 204 patients extracted DNA was genotyped for the rs5210 polymorphism. SPSS software was used for statistical analysis, including t-tests, HWE, genotyping, and multiple logistic regression analysis. Results The t-tests performed on T2DM cases and controls revealed a significant association in age, weight, BMI, FBG, Hb1Ac, SBP, DBP, HDLC, TC, and TG parameters (p < 0.05). HWE analysis found to be in consistent with rs5210 polymorphism. Allelic association was found in the rs5210 polymorphism (OR-1.64 [95 %CI: 1.08–2.49]; p = 0.01); however, no association (p > 0.05) was observed in the multivariate logistic regression assessment performed in this study. Conclusion These results indicate that the rs5210 polymorphism was primarily associated with allele frequencies, which could be attributable to the small sample size. Large sample size studies will be required to determine whether KCNJ11 gene polymorphisms may be required as a risk marker for T2DM in the Saudi population.

Introduction
Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by low insulin secretion, low insulin action, and high blood glucose levels (Alharbi et al., 2016). Diabetes prevalence is expected to expand from 425 to 629 million between 2017 and 2045, according to the IDF. T2DM complications account for 8.5% of total deaths (Alharbi et al., 2021). Individual or combined genetic and environmental variables play a significant impact in the development and progression of T2DM. Advanced age, elevated body mass index (BMI), diet, lack of physical exercise, smoking, abnormal serum levels, and hypertension (HTN) were all considered to be risk factors for T2DM (Khan et al., 2015a). Obesity and Gestational Diabetes Mellitus (GDM) are risk factors for T2DM. Previous studies have confirmed that T2DM and GDM share a similar pathophysiology and genetic vulnerability, and documented studies with genetic polymorphism demonstrated that both T2DM and GDM have significantly correlated with genetic polymorphism .
The main function of genetic factors is to play a role in the development of T2DM, which results in reduced b-cell insulin action. Genetic factors also induce changes in Kir6.2 structure in pancreatic b-cells in KCNJ11 gene polymorphisms, which impacts insulin secretion. Single nucleotide polymorphisms (SNPs) are more likely to be the source of these biological factors, and KCNJ11 is an important candidate gene for the risk of T2DM due to its function in the control of glucose-induced insulin secretion. Chromosome 11p15.1 contains the KCNJ11 gene, which plays an important role in insulin release from pancreatic b-cells that are activated by glucose. The variants in KCNJ11 gene is correlated with lowered depolarization-evoked insulin exocytosis (Khan et al., 2019, Khan et al., 2015b. Numerous SNPs in the KCNJ11 gene, notably rs757110, rs5215, rs5210, and rs5219, have been studied in many types of diabetes, including neonatal diabetes, type 1 diabetes mellitus (T1DM), T2DM, GDM, and post-transplant diabetes mellitus (Khan et al., 2019, Khan et al., 2015b, Ko et al., 2012, Abbasi et al., 2012. Previous studies documented all SNPs in the Saudi population (Alsmadi et al., 2008) except for rs5210 polymorphism in the KCNJ11 gene, which is one of the reasons for designing this study with rs5210 polymorphism, and the importance of rs5210 polymorphism is currently being studied in worldwide studies. The aim of this study is to examine at the genotyping levels of rs5210 polymorphism in the KCNJ11 gene in older population with T2DM in the Saudi population.

Study plan
This case-control study was carried out in a local community of 204 participants, who were classified into 102 T2DM patients and 102 controls. In this study, an equal number of T2DM cases and controls were chosen for each gender. The study participants with T2DM cases were between the age range of 50-85 years of old. T2DM cases and controls were collected from diverse regions within the Kingdom. The sample size for both T2DM cases and healthy controls was estimated using survey system criteria and an online tool, with 97 subjects in the T2DM cases and controls groups participating (Alfaifi, 2021). Based on American Diabetes Association criteria, 102 T2DM cases were recruited. The inclusion criteria for T2DM cases were confirmed, since the patients had fasting blood glucose (FBG) levels of 7.0mmol/l or higher. The exclusion criteria of T2DM was ruled out if the patient's FBG levels fell into the group of impaired fasting glucose or even normal glucose levels. All diabetic patients in this study were diagnosed with T2DM before or after an average of 5 years. Healthy controls (n=102) were selected based on normal glucose levels without any history of any form of diabetes. The exclusion criteria were categorized as patients had excessive glucose levels, were diagnosed with other metabolic disorders, or were on metformin medications. Ethical grant was obtained for this study. Signed informed consent form participants were involved in this study.

Measurements of participants and blood sampling
For T2DM cases and controls, age is recorded in years, gender is documented as male or female, height is measured in centimeters (cms), and weight is recorded in kilograms (kg). BMI was determined using weight and height using the formula BMI=kg/m 2 (Alharbi et al., 2020). Normal, overweight, and obese levels were classified based on BMI values. In this study, 5ml of venous blood was collected for biochemical and molecular analysis in an anticoagulant ethylenediaminetetraacetic acid (EDTA) vacutainer and also in coagulant tubes. Serum was separated for biochemical processes, and human DNA was isolated using EDTA blood. Systolic and diastolic blood pressure (SBP and DBP) readings were used to assess HTN (Alharbi et al., 2014).

Biochemical assays
Serum was extracted from the coagulant tubes and used for biochemical assays such as FBG and lipid profiles for total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC). Furthermore, glycated hemoglobin (Hb1Ac) levels were determined from blood collected in an EDTA vacutainer. Biochemical analysis was performed with an automated assay (Alharbi et al., 2017).

Genotype determination
Two hundred and four EDTA blood samples were used to extract human DNA using a kit-based procedure that followed the manufacturer's recommended protocol (Qiagen, USA). The isolated DNA was diluted in 200ml of TE buffer before being placed onto a 1% agarose gel. The samples were afterwards maintained at À20°C until the polymerase chain reaction analysis process was completed. The PCR process is initiated with a genotyping examination of the rs5210 polymorphism in the KCNJ11 gene. The target SNP locus rs5210 polymorphism was amplified in a single system utilizing a PCR machines thermal cycler. The PCR process used 50ml of reaction, which included 20ml of PCR master mix, 1ml of diluted forward/reverse primers, 23ml of purified water, and 5ml of genomic DNA. The primers were adapted from the previous studies (Khan et al., 2015b). The PCR program for the rs5210 polymorphism was as follows: initial denaturation at 95°C for 10 minutes, 40 cycles of total reaction with the remaining processes as denaturation at 94°C for 1 min, 64°C for 1 min as annealing temperature, 72°C for 1 min as extension, and 10 min to complete the final extension at 72°C. Following the end of the genotyping process, a 152bp PCR product was obtained, and a 2% agarose gel was utilized to check the PCR product using a 100bp DNA ladder. The amplified PCR products were digested using the HPY1888III restriction enzyme. The restriction digestion analysis lasted 18 h at 37°Celsius, and the digested products were 96/54 bp for the GG genotypes, 152 bp for the AA genotypes, and 152, 96, and 54 bp for the heterozygous genotypes. The digested PCR products were run on a 2% agarose gel stained with ethidium bromide once again. Validation was confirmed with Sanger sequencing analysis (Al-Otaiby et al., 2021).

Statistical analysis
SPSS software was used for the statistical analysis (25th version, USA). All clinical and genotype data were gathered in Excel and then converted to SPSS files for the convenience of performing the student t-test, Hardy Weinberg Equilibrium (HWE), and genotyping analysis for the rs5210 polymorphism between diabetic cases and controls. Furthermore, in diabetic cases, multiple nominal regression analysis was performed using FBG as the reference. Continuous variables are represented by the mean and standard deviation, while categorical variables are represented by percentages. When comparing two groups, a p value of <0.05 indicates a significant correlation (Khan et al., 2019).

Results
In this study, 204 Saudi participants were involved, with 102 experiencing T2DM and the remaining 102 as healthy controls. The analysis of this study was sub-divided into the following groups as follows

Basic characteristics of 204 Saudi subjects
The clinical details of T2DM cases and healthy controls were shown in Table 1. Both, T2DM and healthy controls had minimum and maximum ages of 50-85 years and 40-80 years, respectively. A substantial association was discovered based on the mean ages of both groups (p < 0.0001). The gender was selected equally for both the subjects and showed no association (p=1.00). T2DM cases had a mean weight of 75.4 ± 11.15, whereas controls had a weight of 70.1+10.63, indicating a positive association (p = 0.006); it also shows in obese T2DM cases and overweight controls (p = 0.0001). The association between glucose levels in the blood and FBG and Hb1Ac levels was high. SBP and DBP levels were both found to be substantially associated. Among the lipid profiles, HDL-C, TC, and TG levels were greater in T2DM patients, with a significant association (p<0.05). Height and LDL-C levels were consistently similar in T2DM cases and controls and documents the negative association (p > 0.05).

Multiple logistic regression analysis
Multiple logistic regression analysis was used in this study with anthropometric and biochemical variables considering FBG as dependent factors and Age, Weight, BMI, Hb1Ac, SBP, DBP, HDLC, LDLC, TG, and TC as independent variables. When genotyping values were eliminated, none of the factors demonstrated a positive association (Hb1Ac; OR-0.10;95%CI:0.19-0.67; p=0.28 and TC; OR-0.10; 95%CI: 0.16-0.56; p=0.28). The multiple logistic regression analysis is described in Table 4. Furthermore, Fig. 1 illustrates FBG levels in the form of histograms, while Fig. 2 represents a scatterplot with FBG as the dependent variable, indicating that FBG levels were found to be higher in T2DM patients.

Discussion
Diabetes has become a prevalent condition in the modern era, and according to the 8th edition of the Diabetes Atlas, around 425 million individuals aged 20-79 suffer from all forms of diabetic diseases. T2DM is a chronic metabolic disorder which is very common in the 20th century due to the uncontrolled diet, lack of physical activity and with the sedentary life style. Additionally, genetics also plays a role in every inherited families (Khan, 2021). According to the International Diabetes Federation, if preventive measures are not adopted, half of the Saudi population would be diabetes by 2030. Diabetes has reached epidemic proportions in Saudi Arabia (Robert and Al Dawish, 2020). Approximately 1.1 million children and adolescents under the age of 20 are expected to be affected by type 1 diabetes in Saudi Arabia, which ranks eighth internationally in terms of total cases and fourth in terms of incidence as it has 33.5/0.1 million cases (AlHaidar et al., 2020).
The current study results concur a positive association in the form of allelic association (OR-  as age, weight, and BMI, as well as biochemical analysis FBG, Hb1Ac, and lipid profile parameters such as HDLC, TC, and TG, revealed elevated levels with a statistical association among T2DM cases (p < 0.05). None of the variables exhibited a positive correlation using multiple logistic regression analysis in T2DM cases when FBG was assessed as the dependent parameter (p > 0.05). The rs5210 polymorphism was found to be significantly associated with Khan et al studies (Khan et al., 2015b) in an Indian population, which was confirmed by VKhan et al  and Liu et al (Liu et al., 2006) studies. In an Indian population with GDM and PTDM, this rs5210 polymorphism was found to be associated (Khan et al., 2019, Khan et al., 2015b. Sakamoto et al reported rs5210 polymorphism to be associated with T2DM in a previous Japanese study (Sakamoto et al., 2007). A previous metaanalysis studies was conducted with a group of SNPs in which E23K and rs5210 polymorphisms were often observed, and it was established that the rs5210 polymorphism was associated with T2DM (Qin et al., 2013. However, the current study was not in accordance with previously documented studies, and the current study was supported by a group of previously recorded global studies , Sakamoto et al., 2007, Al Hussieny and Alsahlawi, 2021, Koo et al., 2007, Malekizadeh et al., 2021, Willer et al., 2007, Cruz et al., 2010, Č ejková et al., 2007. The rs5210 polymorphism was also studied in children with T1DM (Blasetti et al., 2020). Xu et al studies confirmed rs5210 polymorphism was associated with improved clinical efficacy of gliclazide (Xu et al., 2009).
Diabetes can be caused by both pathogenic and non-pathogenic genetic mutations. SNPs, which are non-pathogenic mutations, have been associated to several types of diabetes susceptibilities. The decrease in ATP ability to inhibit K ATP channel activity, along with an increase in MgATP's ability to simultaneously stimulate this channel function via the voltage-dependent potassium chan-  nel, results in the closure of voltage-dependent calcium channels. Diabetes can be induced by mutations in the KCNJ11 gene, which reduces the capacity of ATP to block K ATP channel activation. The rs5210 polymorphism is present on 3 0 UTR region located at chromosome location 17,386,704 with documented 0.46 as minor allele frequency. Insulin exocytosis is important for blood glucose regulation, and miRNAs have been found to regulate insulin exocytosis in pancreatic b-cells (Haghvirdizadeh et al., 2015). SNPs in KCNJ11 gene has been studied in various forms of diabetes such as NDM, T1DM, T2DM, GDM and PTDM (Abbasi et al., 2012, Koo et al., 2007, Khan et al., 2019, Khan et al., 2015b. Glycated hemoglobin (Hb1Ac) is produced by the irreversible post-translational non-enzymatic interaction of the aldehyde group of glucose and other hexoses with the amino terminal valine of the hemoglobin b-chain (Chandalia and Krishnaswamy, 2002). Hb1Ac has been shown to be an everlasting approach for evaluating glycemic management and monitoring blood glucose levels. The majority of global studies found a significant strong correlation between Hb1Ac and mean glucose levels, and some studies confirmed that Hb1Ac can be utilized as a diagnostic marker in diabetes patients (Kostov and Blazhev, 2020). In the current study, the mean levels of Hb1Ac was found to be 7.7±0.88 and 5.5±0.62 in controls.
This study confirms both the studies strengths and limitations. The strength of this study was participants were recruited from Saudi community, followed diabetic subjects based on ADA criteria and reconfirmed T2DM patients based on FBG and Hb1Ac levels. The limitation of this study can be confirmed as low sample size and studies only rs5210 polymorphism without documenting any medication history in T2DM patients.

Conclusion
The KCNJ11 gene polymorphism rs5210 polymorphism was shown to be the sole source of allelic association in this study. There may be many explanations for this, but this study proposes that future studies be conducted in large cohorts and that rs5210 polymorphism should be explored globally to rule out the diagnostic marker for various types of diabetes from infants to adults. There should be regular updates to the meta-analysis in global studies with all the SNPs involved in KCNJ11 gene.


Biopolymeric nanoparticles based effective delivery of bioactive compounds toward the sustainable development of anticancerous therapeutics

Nowadays, effective cancer therapy is a global concern, and recent advances in nanomedicine are crucial. Cancer is one of the major fatal diseases and a leading cause of death globally. Nanotechnology provides rapidly evolving delivery systems in science for treating diseases in a site-specific manner using natural bioactive compounds, which are gaining widespread attention. Nanotechnology combined with bioactives is a very appealing and relatively new area in cancer treatment. Natural bioactive compounds have the potential to be employed as a chemotherapeutic agent in the treatment of cancer, in addition to their nutritional benefits. Alginate, pullulan, cellulose, polylactic acid, chitosan, and other biopolymers have been effectively used in the delivery of therapeutics to a specific site. Because of their biodegradability, biopolymeric nanoparticles (BNPs) have received a lot of attention in the development of new anticancer drug delivery systems. Biopolymer-based nanoparticle systems can be made in a variety of ways. These systems have developed as a cost-effective and environmentally friendly solution to boost treatment efficacy. Effective drug delivery systems with improved availability, increased selectivity, and lower toxicity are needed. Recent research findings and current knowledge on the use of BNPs in the administration of bioactive chemicals in cancer therapy are summarized in this review.

Nowadays, e ective cancer therapy is a global concern, and recent advances in nanomedicine are crucial. Cancer is one of the major fatal diseases and a leading cause of death globally. Nanotechnology provides rapidly evolving delivery systems in science for treating diseases in a site-specific manner using natural bioactive compounds, which are gaining widespread attention. Nanotechnology combined with bioactives is a very appealing and relatively new area in cancer treatment. Natural bioactive compounds have the potential to be employed as a chemotherapeutic agent in the treatment of cancer, in addition to their nutritional benefits. Alginate, pullulan, cellulose, polylactic acid, chitosan, and other biopolymers have been e ectively used in the delivery of therapeutics to a specific site. Because of their biodegradability, biopolymeric nanoparticles (BNPs) have received a lot of attention in the development of new anticancer drug delivery systems. Biopolymer-based nanoparticle systems can be made in a variety of ways. These systems have developed as a cost-e ective and environmentally friendly solution to boost treatment e cacy. E ective drug delivery systems with improved availability, increased selectivity, and lower toxicity are needed. Recent research findings and current knowledge on the use of BNPs in the administration of bioactive chemicals in cancer therapy are summarized in this review. KEYWORDS biopolymeric nanoparticles, cancer treatment, drug delivery, nanomedicines, natural bioactives Introduction Non-communicable diseases, such as cancer, are one of the leading causes of death worldwide. The most common type of cancer is lung cancer, which is followed by breast, prostate, and colon cancer (1). Within the next two decades, the number of new cases is expected to increase by almost 70% (2). Present treatment options for cancer include surgery, chemotherapy, and/or radiation therapy. But there are some challenges associated with the above treatment strategies like radiation therapy or chemotherapeutic drugs not only damage cancerous cells, but also harm healthy cells (3). The degree of side effects may vary from person to person depending on the type of cancer, and other variables. Chemotherapy hinders the DNA synthesis in fast-dividing cancer cells, leading to their death. It leads to various side effects as it affects healthy cells of the body (4). Additionally, high drug doses used during chemotherapy lead to increased toxicity to normal cells, with the risk of development of drug resistance (4). Thus, a major task is to strengthen the selectivity of anticancer drugs against cancerous cells while sparing normal cells and tissues. In order to treat cancer, efficient targeted delivery methods of chemotherapeutic drugs or anticancer bioactive molecules are also required. In view of the above facts, a potential approach was used to target tumor cells through nano-medicine-based preparations (5). These preparations consist of ultra-micrometer-sized carriers having the bioactive compound(s) that are capable of selectively treating tumors, thus, improving the therapeutic value of the anticancer drugs that are being used.
For the past decade, nanoparticles (NPs) have become tremendously appealing for use in biomedicine. Through enhanced permeability and retention (EPR) effects in tumor tissues, nanoparticle-based drug delivery techniques or nanocarriers can improve therapeutic efficacy and selectivity (6). Nanocarriers also have superior cellular uptake as compared to standard chemotherapeutic molecules. Among the nanocarriers, polymeric NPs, micelles, and liposomes have received significant attention (7).
The polymers utilized to prepare polymeric NPs such as poly (methyl methacrylate), polystyrene, polyacrylates, and polyacrylamide were not eco-friendly (8). The nanosystems prepared by these materials displayed chronic toxicity and inflammatory reactions. The use of new nanosystems might have huge interest to accomplish additional applications for the current large-scale characterized bioactive compounds. Nanoencapsulation, in actuality, is a low-cost technology that could allow for regulated bioactives release, which could be useful in cancer treatment. There are synthetic and natural biodegradable polymers. Polymeric nanoparticles have been created using naturally occurring biodegradable polymers, such as alginate, gelatin, chitosan, and others (9). Some researchers studied about targeted delivery systems of therapeutics through chitosan and other biopolymer based NPs for cancer therapy (10, 11). Therefore, this review focuses on recent progresses in the development of BNPs for the effective delivery of bioactive chemicals for targeted therapy of cancer.

Bioactive compounds
Bioactive substances are a natural occurrence as well as a part of our diet. Plants produce phytochemicals, which are natural bioactives capable of regulating metabolic processes and promoting good health (12). Amino acids, vitamins, enzymes, fibers, minerals, essential oils, and polyphenols are among the plant-based bioactive compounds (13). Natural biopolymers also consist of plant-derived or animal polysaccharides and proteins as well as polymers of microbial (bacteria, fungi, and yeast) sources. Several bioactive substances have the potential to be used as cancer chemotherapeutic drugs in past few years. Phytochemicals like vinca alkaloids, cephalotaxus, berberine, combretastatins, colchicine, ellipticine, and others are known for anticancerous activities against many cancer types (14). A flavonoid, chicoric acid isolated from Echinacea purpurea act as an immune stimulant by increasing the number of natural killer cells (15). A sulfur-containing compound called Ajoene isolated from Allium sativum suppresses the rate of cancer development. In a study, Shang et al. (16) reported the role of ajoene in the suppression of the growth of human breast cancer cells. Likewise, curcumin, an active chemical derived from the Curcuma longa plant, has anticancer properties. It caused the transcription factors AP1, NFkB, and STAT3 to be inhibited, halting the cell cycle in the G2/M phase (17). Similarly, another anticancer agent like Lappaol F has been obtained from Arctium lappa L. and has arrested the G2 phase of the cell cycle by promoting the G1 phase in which the p21 gene plays an important role for the same Lappaol F (18).
Citral is a bioactive ingredient found in citrus-based plant Cymbopogon citratus. Nanostructured lipid carriercitral showed effective results against MDA-MB−231 breast cancer cells (19). Several researchers reported promising bioactive components from Cannabis sativa like delta 9tetrahydrocannabinol (THC) and cannabinoids (CBD) which have also been investigated for their potential to treat cancer in both in vivo and in vitro studies (20-22).
A compound wedelolactone, isolated from Eclipta alba involve in the inhibition of T47D, MCF−7, and MDAMB−231 cells by exciting ER signaling (23). Curcumin is another important bioactive obtained from Curcuma longa which contains curcuminoids compounds (24). Curcumin is known to have low bioavailability because of its poor absorption and fast removal from the body. Basniwal et al. (25) have used NPs mediated delivery of curcumin to increase its bioavailability. Curcumin has been reported as a potent anticancer agent on various types of human cancers such as lung, pancreatic, prostate, breast, ovarian and others (26). Another bioactive .
/fnut. . myricetin is a bioflavonoid commonly present in food sources such as berries, red wine, vegetables, tea, and medicinal plants which is a promising anti-carcinogen with therapeutic potential reported in the breast (27), colon (28), liver (29), ovarian (30), and skin cancers (31). Geraniin is a dehydroellagitannin that is found in a variety of medicinal plants and is thought to be the most active natural chemical. Geraniin was discovered from the fruit of the Phyllanthus emblica L. plant, and found to have potent antioxidant, antimicrobial, and anticancer properties (32, 33). On MCF7 human breast cancer cells, geraniin was found to have an anticancer impact (34). The two major classes of fat soluble antioxidants in Vitamin E are tocopherols and tocotrienols (T3) (35) that showed anticancerous properties against skin (36), stomach (37), liver (38), breast (39), colon (40), lung (41), and prostate cancer (42). Anticancer activity has been documented for a number of biologically active substances ( Table 1).

Development of biopolymeric nanomaterials
Biopolymer composites integrate the necessary qualities of two or more acceptable materials to improve the physiological and mechanical needs of biomedical regions. Because of their long-term stability, chemical substances utilized in standard processes to produce polymeric nanomaterials may cause environmental impact. Biopolymers, on the other hand, are frequently created from non-toxic monomers and are carbonneutral. It is easier to make nanomaterials from biopolymers since they are deposited at the nanoscale. Biopolymers have been found in plants, algae, fungi, bacteria, and animals. Macromolecules include starch, alginate, chitosan, dextran, and chitin ( Figure 1). There are several compounds like pectin, cellulose, lignin, and hyaluronic acid, that are used to create nanomaterials composites. In the medical field, such as in the treatment of cancer, nano biocomposites have shown encouraging outcomes in recent years such as biodegradable substances, and chitosan nanoparticles are employed to deliver anticancer drugs (58). Biopolymers are made up of diverse components and have varied physiological properties. Biopolymeric nanomaterials can be made by attaching metals to biopolymers. To construct molecular capsules, biopolymers, in particular, utilize intramolecular hydrogen bonding. Starch, for example, can be used to create polymeric nanocomposites by combining metals or metal oxides. Chitosan is also used in nanotechnology applications because of its extensive compatibility (59). To make nanomaterials, silver (Ag) can be supramolecularly incorporated into starch (60). Nanomaterials can be incorporated into biopolymers by impregnation or absorption. Physical features of NPs can differ from macro-sized bulk materials due to their greater surface area and reactivity. Nanocapsules or nanospheres can be manufactured depending on the manufacturing approach .
/fnut. .   Frontiers in Nutrition frontiersin.org . /fnut. . (61). Spectroscopy, microscopy, and others are among the techniques used for NPs characterization. Biopolymers and their derivatives are widely utilized, and studied in the creation of hydrogels. Chemical and physical methods of producing biomaterial-based hydrogels can be distinguished. The chemical process of incorporating substituent groups into biopolymer structures, strengthening and developing new functional bioactivities as a result. Covalent bonds between the utilized polymers are created via free radical polymerization, graft copolymerization, and other polymerization techniques (6,62,63). The chemical reaction within the hydrogel creates everlasting bonds in the polymer system. However, reversible physical interactions such as van der Waals attraction, hydrogen bonding, polymer chain entanglements, ionic interactions, and crystallite associations hold the hydrogels together during the physical process (64). There are several nanomaterials based biopolymers employed for effective delivery of bioactives for cancer therapy (Table 2).

Targeted delivery of bioactives via biopolymeric nanoparticles for cancer therapy
According to the World Health Organization, cancer is one of the leading causes of mortality, with more than twenty million people expected to die by the year 2025 (1). Chemotherapeutic medicines work by interfering with DNA synthesis in rapidly dividing cancer cells, slowed DNA replication, reducing therapeutic efficacy and generating a significant mortality rate in cancer patients due to their large doses (4). Bioactive molecule sources and development, as well as their involvement in drug delivery systems and molecular mechanisms against different cancer cells, are illustrated in (Figures 2A-E). Natural bioactive chemicals have an impact on cellular metabolism and signaling pathways, and they can be used to cure cancer ( Figure 2C). Natural bioactive chemicals have a favorable effect on cancer treatment, according to results from both in vivo and in vitro trials (10). A study reported in cancer reports showed that resveratrol NPs has enhanced anticancer activity both in vitro and in vivo (77). Biopolymers as NPs are increasingly being employed as a different way to deliver bioactive compounds/drugs or biological macromolecules to specific body regions. Polymer nanoparticles are a novel way of medication delivery. As a result, the primary goal of biopolymerbased nanomedicine is to deliver therapeutics just to cancer cells, increasing efficacy while reducing toxicity. Nanoparticles containing natural bioactives for targeted medication delivery in various tissues enhanced bioavailability, reduced side effects, improved in vivo stability, and improved target-specific activity of bioactive chemicals in cancer treatment. In the year 2020, Mousa et al. (78) reported that nanoformulation of 3, 3 ′ -diindolylmethane (DIM) and ellagic acid showed more effective suppression of cell viability in pancreatic cancer, tumor weight, and tumor angiogenesis as compared to with these bioactive compounds alone. New formulation strategies on lipid-based delivery systems as nanocarriers also showed improved bio-efficacy under in vivo conditions (79). Biopolymer-based nanocarriers, liposomes, dendrimers, lipid-based NPs, polymeric micelles, and other new drug delivery technologies have been discovered in the last two decades that allow bioactive chemicals to be delivered into the site of action (80). Proteins (albumin, gelatin, and milk proteins), polysaccharides (cellulose, starch, pectin, chitosan, dextran and sodium alginate), and nucleic acids are examples of biopolymers (81). Biopolymer NPs were found to be effective in delivering bioactive chemicals to malignant cells in both in vivo and in vitro investigations. Biopolymeric nanoparticles containing bioactive substances have several advantages over other current delivery technologies, including non water-soluble drug delivery, stability protection, and targeted medication delivery to specific tumor cells (82). Nanoparticles deliver the therapeutic chemical, which could be natural bioactive or synthetic, directly into the target tissue/organ. Nanoparticles have a lot of potential as molecular transporters since they can deliver treatments to malignant cells without harming healthy cells (83). Polymeric pharmaceuticals, polymeric micelles, polyplexes, polymer-drug conjugates, and polymerprotein conjugates are all examples of biopolymers utilized in therapy (84).
The ways NPs are administered, as well as their physicochemical properties, have a big impact on therapeutic efficacy and biological consequences ( Figure 2C). Every mode of administration has advantages and disadvantages, but the oral route of delivery is the safest and most convenient way to treat cancer. The oral mode of administration, on the other hand, has drawbacks such as gastrointestinal degradation, insolubility, and reduced absorption. As a result, current anticancer compositions aren't suited for use as oral chemotherapy. The use of biopolymers for oral delivery platforms has the potential to overcome some of the problems associated with the delivery of chemotherapy drugs. Biopolymeric formulations prevent NPs from pH degradation, enhance water solubility and stability, and target particular binding sites for selective absorption and drug release ( Figure 2D) (85). Future formulations from diverse plants with anticancer properties could significantly boost the potency of anticancer medications for cancer therapy (9). The potency of recognized naturally occurring bioactive chemicals has been increased through the use of nanomaterials. In the future, herbal compounds might play a bigger role in the delivery mechanism for nano biocomposites mediated therapeutic molecules. Further research is required in this area.

Challenges and future perspectives
Every day, there are large number of patients who have advance tumors and most common concern regarding the therapy is the effectiveness and the expense of cancer medication. The effectiveness and cost of pharmaceuticals have not altered dramatically as a result of the development of new technology and drugs. Not only is the efficacy of new treatments a source of concern in India; but wealthier countries such as the United States and Europe are also experiencing issues with cancer drug delivery systems. Nanotechnology is one of the most exciting fields in the area of drug delivery systems to treat non-curable cancer disorders, especially in such a crucial situation. Nanoparticles are utilized to target and deliver drugs to cancer/tumor cells while preserving the physiology of non-tumorous cells. Researchers are working to make more consistent NPs so that the right amount of harmless therapeutics can be delivered to the right place. Metal-based (gold and silver) NPs production has progressed significantly for their applications in diagnostic and therapeutic purposes. The understanding of treatment mechanism at the molecular level will expand bioactive compounds applications for cancer therapy. Because of the regulated release of specific medications at targeted places, assessment of events during drug interaction at the tissue/cellular level, and prediction has not yet been found completely, and its application in cancer therapy/diagnosis is still limited. Animal research will provide important information on the possible use of nanoformulations as medicinal therapeutics. Acute and chronic studies are required to assess the possible harm of any type of anticancerous therapeutic molecule to humans and the environment, and their affordability is another area of research that requires further input.

Conclusions
Drugs have numerous obstacles, thus researchers are focusing on herbal medicine to reduce drug side effects and improve their effectiveness through the use of appropriate effective delivery systems. Preclinical and in vitro investigations have revealed that NPs are particularly effective at delivering chemotherapeutic medicines, molecules as well as natural components to specific tumor sites. Nanoparticles have significant advantages over alternative drug delivery systems in terms of high specificity, high stability, controlled drug release, and high drug-carrying capacity, and the ability to transport both hydrophobic and hydrophilic drug molecules. Because of their controlled release, subcellular size, and biocompatibility with cells, polymeric NPs are now widely used as drug/anticancer bioactives delivery systems in the pharmaceutical and medical areas for cancer therapy.


On the nature of the plant ER exit sites

In plants, the endoplasmic reticulum (ER) and Golgi bodies are not only in close proximity, but are also physically linked. This unique organization raises questions about the nature of the transport vectors carrying cargo between the two organelles. Same as in metazoan and yeast cells, it was suggested that cargo is transported from the ER to Golgi cisternae via COPII-coated vesicles produced at ribosome-free ER exit sites (ERES). Recent developments in mammalian cell research suggest, though, that COPII helps to select secretory cargo, but does not coat the carriers leaving the ER. Furthermore, it was shown that mammalian ERES expand into a tubular network containing secretory cargo, but no COPII components. Because of the close association of the ER and Golgi bodies in plant cells, it was previously proposed that ERES and the Golgi comprise a secretory unit that travels over or with a motile ER membrane. In this study, we aimed to explore the nature of ERES in plant cells and took advantage of high-resolution confocal microscopy and imaged ERES labelled with canonical markers (Sar1a, Sec16, Sec24). We found that ERES are dynamically connected to Golgi bodies and most likely represent pre-cis-Golgi cisternae. Furthermore, we showed fine tubular connections from the ER to Golgi compartments (ERGo tubules) as well as fine protrusions from ERES/Golgi cisternae connecting with the ER. We suggest that these tubules observed between the ER and Golgi as well as between the ER and ERES are involved in stabilizing the physical connection between ER and ERES/Golgi cisternae, but may also be involved in cargo transport from the ER to Golgi bodies.

Introduction
In plants, the Golgi apparatus (GA) comprises many distinct stacks of membrane-bounded cisternae, approximately 1 micron in diameter that tend to be distributed around the cytoplasm. In many cell types, especially highly vacuolated cells, Golgi stacks are motile (Boevink et al., 1998) and closely associated with the endoplasmic reticulum (ER). This close association has been demonstrated by the application of optical laser tweezers, which can trap individual Golgi bodies and pull strands of attached ER behind them (Sparkes et al., 2009). Attachment to the ER however may not occur via membrane connections, such as hemifusion, as it has been shown that AtCASP, a member of the golgin family of proteins, may act as a proteinaceous tether between the ER and Golgi (Osterrieder et al., 2017). Due to this very close association between the ER and Golgi bodies, it was proposed that the cargo exit sites on the ER surface (ER exit sites, ERES) and the Golgi comprise a secretory unit that travels over or with a motile ER membrane (daSilva et al., 2004). The close association between the ER and Golgi bodies raises the question of the nature of the transport vectors carrying cargo between the two organelles.
It is generally accepted that most cargo from the ER reaches the Golgi via mechanisms dependent on the COPII machinery (for recent reviews see (Brandizzi, 2018;Kurokawa and Nakano, 2019;Robinson, 2020;Kriechbaumer and Brandizzi, 2020). COPII proteins are a set of functionally conserved proteins such as the cytosolic small GTPase Sar1, the ER membrane protein guanine nucleotide exchange factor (GEF) Sec12 and components of the COPII coat Sec23/24 and Sec13/31. Retrograde transport back from the Golgi bodies to the ER well as retrograde transport within the Golgi apparatus is facilitated by the COPI machinery (Oprins et al., 1993;Arakel and Schwappach, 2018;Robinson, 2020). COPI vesicles were identified by immunogold labelling of cryosections using antibody-labelling of COPI components such as the GTPase ARF1 and different coatomer subunits (Orci et al., 2000;Pimpl et al., 2000;Donohoe et al., 2007;Langhans et al., 2012) but COPII vesicles have been rarely observed (Langhans et al., 2012), raising the question on the identity of the carriers operating in ER-to-Golgi transport.
Indeed, it appears that several types of carriers (tubules, saccules, tunnels, and coated vesicles) may coexist and operate along the ER-to-Golgi route allowing for a diverse, flexible and robust trafficking system. For instance in mammalian cells, using 3D electron-tomography (Zeuschner et al., 2006) it was shown that ERES are continuous with the ER and capable of adapting in size depending on the secretory load (Farhan et al., 2008;Boncompain et al., 2012;Weigel et al., 2021;Shomron et al., 2021). It was previously suggested by the metazoan and yeast research communities that the anterograde vectors for general cargo are COPII-coated vesicles produced at ribosomefree ERES and COPII coated tubules could carry larger proteins (Gorur et al., 2017). COPII vesicles and tubules would then deliver cargo directly to the cis-Golgi in yeast (Matsuura-Tokita et al., 2006) or to an intermediate vesiculo-tubular compartment that is transported over varying distances to the cis-Golgi in animal cells (Tang et al., 2005). However, various reports suggested that ER-to-Golgi transport requires both vesicular and tubular compartments to sort the ERES cargo to the Golgi apparatus (Saraste and Svensson, 1991;Bannykh et al., 1996;Xu and Hay, 2004;Watson and Stephens, 2005). Assays with temperature-sensitive fluorescently tagged cargo also showed that cargo colocalizes with COPII components at the ERES but does not exit the ERES with the COPII coat component Sec24, suggesting that at least parts of Golgi trafficking might be COPII independent (Presley et al., 1997;Stephens et al., 2000). Indeed, it was reported that COPII components remain on the ERES and that cargo is transported in Rab1-dependent carriers that are not labelled by COPII proteins (Westrate et al., 2020). These data highlight that vesicle carriers are not the only means for anterograde transport and highlight the possibility that COPII is rather involved in secretory cargo selection than its actual transport.
In support of this, recent data in mammalian cells showed that ERES expand into a tubular network containing secretory cargo but no COPII components. COPII components were found to decorate the neck of these tubules, implicating that the departing transport carrier is not coated (Weigel et al., 2021;Shomron et al., 2021). Based on the findings that COPII does not coat the carriers leaving the ER, it was suggested that COPII helps solely to select secretory cargo.
The plant trafficking community has generally embraced the concept of COPII vesicle vectors, due to the presence of all the structural proteins required for COPII coat construction (Kang and Staehelin, 2008). However, there is little microscopy evidence for the existence of such vesicles (Langhans et al., 2012), and due to the limited space between the ER and cis-Golgi an alternative hypothesis based on direct tubular connections between the two organelles has been proposed and debated over the years (Hawes et al., 2008;Hawes, 2012;Robinson et al., 2015;Kriechbaumer and Brandizzi, 2020).
Here we show that by utilizing high-resolution microscopy in live plant cells and by considering geometry of the donor and acceptor membranes, ERES are associated with the cis-face of Golgi cisternae rather than associated with the ER surface. Moreover, multiple small ER-derived tubules are associated with most Golgi cisternae. Thus, in plants, the nature of the ER-Golgi interface and even the nature of ERES in their currently accepted form should be re-evaluated.

Plant growth and Agrobacteriummediated transient protein expression
Nicotiana tabacum (SR1 cv Petit Havana) plants were grown for transient Agrobacterium-mediated expression, as previously reported (Sparkes et al., 2006). In brief, transformed agrobacteria were pelleted by centrifugation at 1800 g at room temperature for 5 min. Infiltration buffer (5 mg ml −1 glucose, 50 mM MES, 2 mM Na 3 PO 4 ·12H 2 O and 0.1 mM acetosyringone) was used to wash the pellet once and then to resuspend the agrobacteria in 1 ml. The bacterial suspension was diluted in the infiltration buffer to an OD 600 of 0.1. The final dilution of the infiltration medium was injected through the stomata on the underside of the tobacco leaf using a 1 ml syringe. Infiltrated plants were kept at 22°C for 72 hours prior to imaging.
Arabidopsis thaliana (Col-0) plants expressing GFP-HDEL and ST-mRFP in a stable manner were briefly sterilized with 70% ethanol and placed on plates with ½ strength Murashige and Skoog medium. The plates were stratified at 4°C in the dark for 3 days before being transferred to a plant incubator at 22°C with 16 hours light and 8 hours dark.

Confocal microscopy
Transformed leaf epidermal samples were imaged using a Zeiss PlanApo ×100/1.46 NA oil immersion objective on a Zeiss LSM880 confocal equipped with Airyscan detector. Typically 512 × 512 images and time-lapse sequences were collected in 8bit with 2-line averaging at an (x,y) pixel spacing of 20-80 nm with excitation at 488 nm (GFP) and 561 nm (RFP), and emission at 495-550 nm and 570-615 nm, respectively.
Distances between markers were analyzed using Zen line profiles, measuring the distance between the maximum of the corresponding fluorescence peaks. Significance was calculated by Kruskal-Wallis (*p< 0.05; **p< 0.01; ***p< 0.001).

Drug treatments
Segments (roughly 5 mm 2 ) of transformed leaves were used for drug treatment, confocal imaging, and analysis. For inhibition of actin polymerization, leaf tissue was submerged in 25 µM latrunculin B (stock solution: 10 mM in DMSO) for 30 mins. BFA (stock solution: 10 mg ml -1 in DMSO) was used at a concentration of 100 µg ml -1 . BFA washes were performed as described earlier . All stock solutions were kept at -20°C, working solutions were prepared fresh just before use.

High-resolution imaging of the ER-Golgi interface in live plant cells
To obtain high-resolution imaging, we implemented a Zeiss LSM880 confocal microscope equipped with Airyscan detector, which enables up to 120 nm lateral resolution. We imaged cells coexpressing markers for the ER lumen (GFP-HDEL; (Brandizzi et al., 2003)) and the medial/trans cisternae of Golgi bodies (sialyltransferase (ST)-mRFP; ). Proteins were first expressed transiently in tobacco leaf epidermal cells (Sparkes et al., 2006).
We found that Golgi bodies are motile and associated with ER tubules ( Figure 1A; Supplementary movie S1) or curved ER and Golgi are in close association as demonstrated by high-resolution microscopy. The ER marker GFP-HDEL (in green) and the Golgi body marker ST-mRFP (in magenta) are transiently expressed in tobacco leaf epidermal cells. Golgi bodies are associated with ER tubules (A), yellow arrow) and cisternal edges (B, yellow arrow) and can sit in small lacunae within ER cisternae (C, white arrow). Size bars = 1 µm. edges of cisternae ( Figure 1B) or may be trapped within small lacunae in ER cisternae ( Figure 1C). Although connections between ER and Golgi bodies have been described before (daSilva et al., 2004;Sparkes et al., 2009;Osterrieder et al., 2017;Vieira et al., 2020), our results indicate that we can visualize the spatial distribution of the ER and Golgi in live cells at a level of resolution that has not been reported before.

Fine dynamic tubules connect ER and Golgi bodies
Looking at the dynamics and the shaping of Golgi bodies with high-resolution live-cell microscopy, we found that all Golgi bodies visualized produce small membrane protrusions from their surface that are very dynamic but always make contact with or are wrapped around ER tubules ( Figure 2), allowing for a constant physical but highly dynamic connection between the two organelles.
Furthermore, fine ER tubules were seen to thread through Golgi bodies ( Figure 3A time series, Figure 3B) and wrap themselves around Golgi bodies ( Figures 3A, C). These thin tubules average about 20 nm diameter, considerably smaller compared to 40 nm diameter for the average ER tubule (Pain et al., 2019). Almost every Golgi body imaged appears to be attached to the ER via one or two of these ER-derived tubules. These tubules can also connect up to Golgi body protrusions ( Figure 3D), but these are rare event to image and were only observed in approximately 1:1000 Golgi bodies. The morphology and location of these fine ER-derived and HDEL-labelled tubules distinguishes them from the tubules of the bulk ER network. To clearly refer to them, we termed them ERGo (ER-Golgi) tubules in the further text. A schematic representation of ERGo tubules and Golgi body protrusions is depicted in Figure 4A.
To confirm that these tubules were not limited to transient expression in tobacco leaf cells, we also imaged the ER and Golgi body markers HDEL and ST in stable expression in Arabidopsis thaliana plants. Also in this system, the dynamic morphology with ERGo tubules ( Figure 5A) and Golgi protrusions ( Figure 5B) was observed ( Figure 5; Supplementary movie S2).
To investigate if ER dynamics impacts on ER-Golgi tubules, the drug latrunculin B (LatB) was applied ( Figure 6). LatB inhibits actin polymerization and interrupts ER dynamics, resulting in immobile Golgi bodies. LatB treatment also resulted in the enhanced formation of ER cisternae (Pain et al., 2019). After LatB treatment, ERGo tubules were clearly visible but we could not determine if they remained through LatB treatment or were formed de novo. De novo formation of ERGo tubules would indicate that they are not only a physical connection required when ER and Golgi bodies are rapidly moving in the cell.

Distribution of ER exit site markers and Golgi glycosylation enzymes
To further investigate the physical link between ER and Golgi bodies, we wanted to look at a structure located between the ER and Golgi, the ERES. Interestingly, protrusions similar to those previously shown with Golgi markers (Figures 2, 5) were also observed when ERES markers/COPII components were expressed together with the ER marker RFP-HDEL (Wang et al., 2014) (Figures 4B, 7). We used functional fluorescent fusion markers of the COPII coat proteins GFP-Sec24 (Faso et al., 2009), GFP-Sec16 (Takagi et al., 2013) and Sar1a-GFP (Hanton et al., 2008). We found that the structures labelled with these markers showed dynamic protrusions in most cases wrapped around ER tubules or connecting with ER tubules (Figure 7) comparable to the protrusions labelled with the Golgi marker (Figures 1-5).
It is also of great interest that ERES markers/COPII components did not label the ER as one would expect for ER Identification of dynamic Golgi-derived tubules that connect with the ER. Golgi bodies labelled with the medial/trans-Golgi marker ST-mRFP (in magenta) form protrusions (yellow arrow) that can also be wrapped around ER tubules (labelled with GFP-HDEL in green). Markers are expressed transiently in tobacco leaf epidermal cells. Images are shown in time intervals of 0.8 s between the frames and time points are indicated. Size bar = 1 µm.
vesicle budding sites but are closely and dynamically aligned with Golgi cisternae. We next aimed to gain deeper insights on the spatial relationship of the cis-Golgi and the COPII markers using high-resolution microscopy. When coexpressed with the cis-Golgi body marker MNS1 (Liebminger et al., 2009;Schoberer et al., 2014), the ERES markers GFP-Sec24 ( Figure 8A), GFP-Sec16 ( Figure 8B) and Sar1a-GFP ( Figure 8C) labelled a compartment close to MNS1-mRFP, however their localization did not fully overlap ( Figure 8). As a control, MNS1-mRFP was coexpressed with MNS1-eGFP ( Figure 8D). The distance between the three tested ERES markers and the cis-Golgi marker MNS1 was statistically significantly larger than the distance between MNS1-mRFP and MNS1-eGFP ( Figure 8E). This indicates that in plant cells the labelled ERES structures may represent a pre-cis-Golgi compartment with ERGo tubules and protrusions allowing for physical connections to the ER ( Figure 4B).  To further investigate a potential pre-cis-Golgi compartment, we coexpressed the ERES markers Sec24 ( Figure 9A), Sec16 ( Figure 9B) and Sar1a ( Figure 9C) with MNS3, the Arabidopsis ER-a-mannosidase I (MNS3; (Schoberer et al., 2019)). MNS3 has previously been shown to partially colocalize with MNS1 and was suggested to reside in cis-most Golgi membranes, the Golgi entry core compartment (GECCO) (Ito et al., 2017). All tested ERES markers colocalized with MNS3 ( Figures 9A-C). As a control, Changing ER dynamics with latrunculin B (LatB). The ER and Golgi markers GFP-HDEL (green) and ST-mRFP (magenta) are coexpressed in tobacco leaf epidermal cells, tobacco leaf pieces were treated with LatB and videos were taken. Time frames [s] are indicated. Size bars = 0.5 µm.

FIGURE 5
The organization of the ER and Golgi shown in tobacco can also be observed in Arabidopsis transgenic plants. ER tubules wrapped around and through the Golgi body (A, yellow arrow) and dynamic protrusions from the Golgi body (B, yellow arrow) were also observed in stably transformed Arabidopsis thaliana plants. Golgi bodies were labelled with the medial/trans-Golgi marker ST-mRFP (in magenta) and the ER is labelled with GFP-HDEL in green. Size bars = 1 µm.
MNS3-mRFP was coexpressed with MNS3-eGFP ( Figure 9D). The distance between the fluorescent peaks between ERES markers and MNS3 was analyzed and did not significantly differ from the control ( Figure 9E). This confirms our results (Figure 8) of a presence of pre-cis-Golgi compartments with a specific composition of proteins such as the tested ERES/COPII proteins and MNS3.

ERGo tubules are still present after inhibition of ER-to-Golgi transport
We next aimed to investigate a potential role for ERGo tubules in ER-Golgi transport. We analyzed the presence of the ERGo tubules in cells with inhibited ER-Golgi transport. Interfering with COPI coat assembly results in the inhibition of protein transport and a collapse of Golgi body membranes into the ER. The fungal metabolite brefeldin A (BFA) is a commonly used method to inhibit COPI coat formation. In plants, BFA targets a Sec7-type GEF that is necessary for activation of the small COPI GTPase Arf1p (Nebenführ et al., 2000). This leads to the dissociation of COPI coat proteins from Golgi membranes (Ritzenthaler et al., 2002) and the redistribution of Golgi markers, such as ST-GFP/ RFP, to the ER and dilatation of the ER network (Boevink et al., 1998;Saint-Jore et al., 2002).
We aimed to use BFA to see if impairment of ER-Golgi transport would influence the presence of ERGo tubules and Golgi/ERES protrusions, which could be an indicator for a potential function of these structures in ER-Golgi transport. We found that BFA treatment on plants expressing ST-GFP and RFP-HDEL resulted in enhanced ER cisternae formation and as expected, redistribution of the Golgi marker ST-GFP to the ER ( Figure 10). As typical for BFA treatment, small STand HDEL-labelled Golgi body remnants remained (Fujiwara et al., 1988;Driouich et al., 1993;Satiat-Jeunemaitre et al., 1996). Interestingly these remnants were connected to the ER by ERGo tubules and were labelled by both the ER and Golgi body markers RFP-HDEL and ST-GFP (Figure 10, zoom in yellow and blue frame). The distribution of ER and Golgi body marker appears not evenly distributed in places, which could be due to the inhibited transport. ERGo tubules were found in connection with all remnants of Golgi bodies ( Figure 10). This suggests that the physical connection between ER and Golgi body remnants was maintained upon BFA treatment.
We next aimed to test the effect of blockage of the COPII pathway and test the hypothesis that a blockage of the progression of the COPII cycle with a dominant-negative mutant of the COPII GTPase Sar1a  would allow to detect the sites of COPII assembly. We used Sar1a-GTP, a constitutively active (GTP-locked) mutant form of Sar1p from Nicotiana tabacum, which has been shown to inhibit protein transport between the ER and Golgi bodies (Andreeva et al., 1998;Takeuchi et al., 2000;Phillipson et al., 2001;daSilva et al., 2004;Hanton et al., 2008). Here a d e x am e t h a s o n e (D e x ) i n d u c i b l e s y s t e m i n s t a b l y transformed Nicotiana tabacum plants allowing controlled expression of Sar1-GTP  was applied. The ER and Golgi body markers, GFP-HDEL and ST-mRFP respectively, were expressed in these plants. We found that 18 h after Dex-induction, most of the ST-mRFP protein pool was located in the ER with only very few and smaller ST-labelled Golgi bodies remaining (Figure 11). Similar to BFA treatment, Sar1a-GTP expression resulted in enhanced ER cisternal areas, and ST-labelled Golgi stacks were quite tightly engulfed within ER lacunae. The stacks were again still connected to the ER by ERGo tubules but differently from with BFA treatment, the ERGo tubules only showed HDEL labelling with ST-labelled protrusions (Figure 11). ERGo tubules could only be seen in connection with remaining Golgi structures. Sar1a-GTP blocks the uncoating of the COPII coat and the Golgi marker is visible in association but still physically distinct from the ERGo tubules. These results, coupled with the findings that COPI inhibition leads to a redistribution of Golgi markers into the ERGo tubules, indicate that the ERGo tubules may be involved in the cargo transport to the Golgi body.

Discussion
The nature of the ER exit sites together with ER-Golgi transport has been a source for discussion over the years. In yeast and mammalian systems COPII/COPI-dependent transport was the generally accepted mechanism, which was also transferred to plant systems.
In mammalian cells, ERES are morphologically recognized as areas on the rough ER membrane that are devoid of ribosomes and form coated buds, vesicles, and vesicular tubular clusters (Tang et al., 2005). These clusters undergo long-range transport mediated by microtubules to dock with the cis-face of the Golgi apparatus (Tang et al., 2005). ERES are characterized by the components of the COPII-coated membranes, v-SNARES required for docking and p24 proteins as cargo receptors (Strating and Martens, 2009). In yeast, COPII-coated vesicles have been suggested to bud from the ER membrane to transport cargo to very simple Golgi bodies that have the capacity to mature from cis-through to trans-forms (Matsuura-Tokita et al., 2006).
In Embryophyta, early conventional transmission electron microscopy did not show any visible coated ER areas or structures that could be convincingly inferred to be ERES. The application of ultra-rapid freezing techniques combined with tomographic electron microscopy though suggested that a COPII vesicle-mediated transport may exist (Kang and Staehelin, 2008). COPII components were indeed identified in plants using bioinformatics analysis (Robinson et al., 2007) but that does not exclude a non-vesicular localization. Live cell imaging methodologies using fluorescent protein markers showed that Golgi bodies are closely linked with the ER (Boevink et al., 1998;daSilva et al., 2004;Faso et al., 2009;Osterrieder et al., 2017). All of this supported the "secretory unit" concept stating that Golgi and ER exit sites are moving together with the ER (daSilva et al., 2004) and that Golgi biogenesis could be from newly generated exit sites (Hawes et al., 2008).
In vitro experiments using giant unilamellar membrane vesicles incubated with COPII components showed no vesicle formation but bead-like membrane organization (Bacia et al., 2011). Recent findings in mammalian systems also question the exclusivity of vesicular anterograde transport. Two research groups showed independently that carriers leaving the ER are not coated by COPII components and suggested the existence of different parallel carrier types including vesicles but also tubules, saccules and tunnels (Weigel et al., 2021;Shomron et al., 2021). In these studies, ERES expand into tubules, which contain cargo but no COPII components. These can only be found at the neck of the tubules; hence, they proposed that carriers leaving the ER are not COPII coated and that the role of COPII is to concentrate transport cargo into carriers (Weigel et al., 2021;Shomron et al., 2021).
Our analyses using a high-resolution confocal imaging approach have provided new insights into the organization of the ER and Golgi interface. By facilitating a visualization of the ER, COPII markers and Golgi membranes in living cells, we were able to capture structures and their dynamics in a manner that is not possible with ultra-resolution microscopy in fixed cells or cryoelectron tomography. Our analyses allowed us to follow the dynamics of the ERGo tubules, which appear to be thinner tubules compared to the bulk ER tubular network. We also showed that treatment with BFA causes a redistribution of Golgi markers into the bulk ER and the ERGo tubules with Golgi remnants distributed at the ERGo tubules, and that blockage of COPII with Sar1a-GTP leads to the formation of The ERES markers localize at the GECCO. ERES markers GFP-Sec24 (A), GFP-Sec16 (B) and Sar1a-GFP (C) colocalize with MNS3-mRFP. (D) MNS3-eGFP and MNS3-mRFP are coexpressed as a control for full colocalization. Representative confocal images and analysis plots are shown for each combination. The blue box indicates the Golgi body shown enhanced on the righthand side panels (merged images in side view together with line profiles for both markers). Proteins are expressed transiently in tobacco leaf epidermal cells. Size bars = 1 µm. (E) Statistical analysis shows the distance [nm] between fluorescent peak of ERES marker and MNS3-mRFP. Significance was analyzed by Kruskal-Wallis. n = 3 with 5 technical replicas each.

FIGURE 10
Disruption of COPI results in the redistribution of Golgi membranes into the ERGo tubules. The ER and Golgi markers RFP-HDEL (magenta) and ST-GFP (green) are coexpressed and the leaf pieces treated with BFA. Connecting tubules between ER and Golgi remnants are visible (yellow arrows). The blue and yellow boxes in the merge image indicate areas shown in higher magnification below. Size bars = 5 µm.
structures that are connected but not merged with ERGo tubules. It was previously suggested that the BFA-induced Golgi remnants contain a minimal set of cis-Golgi membrane proteins carrying out specific roles at the ER-Golgi interface, such as protein sorting, ER-Golgi tethering, and N-glycan processing. These BFA-induced structures could then be used as a reservoir to quickly produce cis-Golgi cisternae with materials directly from the ER Ito et al., 2012;Robinson et al., 2015;Schoberer et al., 2019), and accordingly, we propose ERGo tubular connections may provide physical stability between the ER and the Golgi as well as a rapid and targeted transport pathway.
Pre-cis-Golgi compartments have been previously suggested for proteins proposed to be involved in ER-Golgi tethering: AtGolgin-84A, which colocalizes with Sar1a (Vieira et al., 2020), as well as AtCASP (Latijnhouwers et al., 2007;Osterrieder et al., 2017) and the Arabidopsis ER-a-mannosidase I (MNS3; (Schoberer et al., 2019)). Our results support the existence of a pre-cis-Golgi compartment where COPII components accumulate rather than accumulating on the ER. The thin tubular connections, observed between ER and Golgi as well as between ER and ERES could be involved in cargo transport as well as in stabilizing the physical connection between ER and Golgi bodies. Although we have no evidence to infer a functional role to the ERGo tubules, the visualization of these new structures and the definition of their spatial distribution in relation to COPII markers and the visualization of a pre-Golgi compartment shed an interesting new light onto the ER-Golgi interface in plants and challenge the existing dogma on the existence of COPII vesicles in plants. So far, in plant systems no elegant ER-Golgi cargo transport assay such as the RUSH methodology (Boncompain et al., 2012) for mammalian systems has been established but this will be of great importance for studying an involvement of ERGo tubules in ER-Golgi transport.

Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.   Disruption of Golgi membranes by inhibition of COPII uncoating leads to a segregation of ERGo tubules from Golgi remnants. The dominant negative mutant Sar1a-GTP is expressed in an inducible manner together with the ER and Golgi markers GFP-HDEL (green) and ST-mRFP (magenta). Imaging was carried out 18 h after dexamethasone (Dex) induction and a time-lapse (0 s, 0.8 s, 8 s) is shown. The yellow boxes in the images indicate areas shown in higher magnification on the right hand side. ERGo tubules and Golgi protrusions are indicated with yellow arrows. Size bars = 1 µm. the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. FB is funded by MSU AgBioResearch [MICL02598]. VK is grateful for funding by the BBSRC [BB/ W011166/1] and Oxford Brookes University. AMG is funded via the Oxford Interdisciplinary Bioscience Doctoral training Programme, CP is funded by Oxford Brookes University.